Summary: Cercare Stroke is an AI-powered imaging solution for brain CT and MRI scans, aiding in stroke detection and treatment planning.

Cercare Stroke utilizes artificial intelligence to analyze brain CT and MRI images, identifying suspected stroke lesions, large vessel occlusions (LVO), and intracranial hemorrhages (ICH). It offers automatic motion correction and generates stroke parametric maps based on perfusion data from previous stroke cases, providing decision support for treatment selection. The product integrates into standard reading environments (PACS), AI marketplaces, or as a standalone third-party application, and can be deployed locally on dedicated hardware or virtualized environments. It processes inputs such as NCCT, MR PWI, MR DWI, and MR T2Flair in DICOM format, producing segmentation and heatmap overlays in DICOM format. Regulatory certifications include CE Class IIb under the Medical Device Regulation (MDR).

Clinicians
Radiologists
Neurologists
Emergency Medicine Physicians
Healthcare Providers

Neurology
Radiology
Emergency Medicine
Neuroimaging
Stroke Care
Neurocritical Care
Neurosurgery
Neurointervention
Neurorehabilitation
Neurovascular Medicine

Europe
United States
Canada
Australia
New Zealand
Japan
South Korea
Singapore
Hong Kong
United Kingdom

English German French Spanish Italian Dutch Danish Swedish Norwegian Finnish

Denmark
United States
Germany
United Kingdom
France
Netherlands
Sweden
Norway
Finland
Australia

Real-time stroke detection
Automated image analysis
Clinical decision support
Patient data management
Telemedicine integration
Workflow optimization
Data visualization
Reporting tools
Alert notifications
Collaboration tools

Advanced analytics
AI-powered diagnostics
Patient engagement tools
Mobile app integration
Cloud storage solutions

Windows Server, SQL Server, 16 GB RAM, 500 GB HDD


Summary: Apollo is an AI-driven software suite by Cerebriu that enhances brain MRI workflows by providing real-time detection of critical conditions, adaptive scanning protocols, and efficient reading prioritization.

Apollo is an AI-based software suite designed to optimize brain MRI workflows. It offers real-time alerts on critical conditions such as infarcts, intracranial hemorrhages, and tumors during scans. The suite includes Smart Priority for real-time detection of acute cases, Smart Protocol for dynamic MRI protocol optimization based on initial findings, and Smart Reading for prioritizing MRI scans based on severity and urgency. These features aim to improve operational efficiency, reduce patient wait times, and enhance diagnostic accuracy in radiology departments.

Radiologists
MRI Technologists
Healthcare Administrators

Neurology
Emergency Medicine
Teleradiology

English Danish German French Spanish Italian Portuguese Dutch Swedish Norwegian Finnish Russian Chinese Japanese Korean Arabic Turkish Hindi Bengali Punjabi

Denmark
United States
Germany
United Kingdom
France
Italy
Spain
Netherlands
Sweden
Norway

Real-time acute case detection during MRI scans

Dynamic MRI protocol optimization based on real-time findings

Intelligent reading support with worklist prioritization

Smart Priority
Smart Protocol
Smart Reading

MRI scanners
AI platforms
Healthcare systems

MRI scanners, AI platforms, Healthcare systems

Encryption at rest
Encryption in transit
RBAC
MFA
Audit logs
2FA
DLP

BAA available
Data de-identification
Data minimization


Summary: StrokeSENS is an AI-powered medical imaging software developed by Circle Cardiovascular Imaging, designed to enhance acute stroke care by automating detection and analysis of large vessel occlusions (LVOs) and ischemic tissue in CT scans.

StrokeSENS utilizes artificial intelligence to process non-contrast CT (NCCT) and contrast-enhanced CT angiography (CTA) images, providing automated Alberta Stroke Program Early CT Score (ASPECTS) assessments and LVO detection. It integrates seamlessly into existing radiological environments, offering real-time notifications and advanced visualizations to support clinicians in rapid decision-making. The software is CE certified (Class IIa) and FDA 510(k) cleared (Class II), with availability in the European Union, U.K., Canada, Australia, and the U.S. for LVO detection. It operates on a subscription or one-time license fee model, based on the number of analyses or installations, with pricing details available upon request.

Clinicians
Radiologists
Neurologists
Emergency Medicine Physicians
Healthcare Providers
Stroke Teams
Medical Imaging Professionals
Hospital Networks
Medical Institutions
Healthcare Administrators

Neurology
Radiology
Emergency Medicine
Neuroimaging
Stroke Care
Acute Care
Medical Imaging
Healthcare It
Artificial Intelligence
Clinical Decision Support

European Union
United Kingdom
Canada
Australia
United States

English French German Spanish Italian Dutch Portuguese Swedish Danish Norwegian

Pricing based on number of analyses or installations; contact vendor for details.

Canada
United States
United Kingdom
Germany
France
Australia
Netherlands
Sweden
Denmark
Norway

AI-powered detection of large vessel occlusion (LVO) on CT angiography (CTA)

Automated ASPECTS scoring for early ischemic changes on non-contrast CT

Visualization of perfusion abnormalities using multi-phase CTA

Real-time notifications for suspected acute stroke cases

Integration with existing radiological environments

Enhanced clinical workflow through AI augmentation

Facilitation of timely patient management decisions

Support for front-line clinicians when advanced imaging is unavailable

Standardization of ischemic tissue assessment

Prioritization of time-sensitive cases requiring vascular treatment

Improved decision-making with cutting-edge AI platform

Optimized patient care through automated workflows

Collaboration and information sharing across stroke teams

Support for routine CT/CTA imaging modalities

Enhanced productivity in stroke care pathways

Integration with existing clinical workflows

Support for acute stroke diagnosis and management

StrokeSENS ASPECTS
StrokeSENS mCTA Perfusion

GE Healthcare
Siemens Healthineers
PACS systems
CT/CTA imaging devices

Dedicated hardware or virtualized environment

CE Marked, Class IIa, MDD
FDA 510(k) cleared, Class II

Real-time notifications
Automated image analysis
Data encryption

Compliance with healthcare data regulations


Summary: contextflow ADVANCE Chest CT is an AI-driven software that assists radiologists in detecting and analyzing lung conditions such as lung cancer, interstitial lung diseases (ILD), and chronic obstructive pulmonary disease (COPD) in chest CT scans.

contextflow ADVANCE Chest CT is a computer-aided detection (CAD) system designed to enhance the interpretation of chest CT scans. It offers features like lung nodule detection and quantification, nodule tracking over time, and quantitative analysis of lung tissue patterns. The software integrates directly into existing PACS systems, providing radiologists with comprehensive insights to improve diagnostic accuracy and efficiency. Additionally, it includes a malignancy Similarity Index (mSI) feature, developed in collaboration with RevealDx, to assess the likelihood of malignancy in detected nodules, aiding in early lung cancer detection and reducing unnecessary procedures. The software is CE Marked and available for clinical use within Europe under the new MDR. ([contextflow.com](https://contextflow.com/2024/05/02/contextflow-targets-early-lung-cancer-detection-by-augmenting-advance-chest-ct-with-malignancy-scoring-from-revealdx/?utm_source=openai))

Radiologists
Medical Imaging Professionals
Healthcare Providers
Clinicians
Medical Institutions
Hospitals
Diagnostic Centers
Medical Imaging Centers
Healthcare Organizations
Medical Imaging Departments

Radiology
Pulmonology
Oncology
Thoracic Surgery
Internal Medicine
Chest Medicine
Respiratory Medicine
Medical Imaging
Medical Informatics
Healthcare Technology

Austria
Germany
Switzerland
France
Italy
Spain
Netherlands
Belgium
United Kingdom
United States

English
German
French
Italian
Spanish
Dutch
Belgian Dutch
UK English
US English
Austrian German

Austria
Germany
United States
United Kingdom
France
Italy
Spain
Netherlands
Belgium
Switzerland

Lung nodule detection and quantification (4-30mm diameter)

Nodule classification: solid, part-solid, non-solid

Lung tissue analysis: segmentation and quantification of lungs, lung anomalies, and image patterns including consolidation, effusion, emphysema, ground-glass opacity, honeycombing, pneumothorax, and reticular pattern

DICOM secondary capture: visualizes lung tissue analysis and nodules in color within native viewer

Reporting: quantifications parsed by structured reporting tools or PACS, also available as PDF download

Nodule tracking over time: monitors changes in detected nodules, indicating percentage growth and doubling time

3D image search: detects and analyzes 19 image patterns, including airway wall thickening, atelectasis, bronchiectasis, blebs, consolidation, cysts, effusion, emphysema, ground-glass opacity, honeycombing, masses, mosaic attenuation, nodules, pneumothorax, pulmonary cavities, reticular patterns, budding, and indistinct patterns

Integration with PACS: results displayed in IDS7, DICOM output including DICOM SR, DICOM SC, and encapsulated PDF, worklist integration, pre-populated reports, and verification workflow integration

IPE (Incidental Pulmonary Embolism) detection

Malignancy scoring via RevealAI-Lung integration

PACS
RIS
VNA
Radiology worklist
RevealAI-Lung

encryption at rest/in transit
RBAC
SSO/SAML
audit logs
2FA

BAA available
consent management
data anonymization/pseudonymization

US and EU cloud regions; on-prem deployment available


Summary: AVIEW COPD is an AI-driven software solution by Coreline Soft that automates the analysis of chronic obstructive pulmonary disease (COPD) using chest CT scans, providing comprehensive segmentation and quantitative assessments to aid clinicians in diagnosis and treatment planning.

AVIEW COPD leverages artificial intelligence to perform automated segmentation of lungs, lung lobes, and pulmonary vascular airways from chest CT images. It offers detailed analyses of COPD phenotypes, including emphysema, fissure completeness, airway, and pulmonary vascular evaluations. The software generates intuitive charts, 3D visualizations, and comprehensive reports, facilitating both clinical decision-making and research. It supports the export of approximately 4,000 analysis results in CSV format and provides detailed reports in PDF and DICOM formats. AVIEW COPD is certified by regulatory bodies such as the FDA, CE, and others, ensuring its compliance and reliability in various healthcare settings.

United States
European Union
South Korea
Japan
Taiwan
Australia
Singapore
Brazil
Canada

English Korean Japanese Chinese German French Italian Spanish Portuguese Dutch Russian Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu

South Korea
United States
Japan
Taiwan
Australia
Singapore
Brazil
Canada
Germany
France

Automated lung, lung lobe, and pulmonary vascular airway segmentation

3D emphysema visualization for disease progression tracking

Quantitative analysis with approximately 4,000 metrics exported in CSV format

Detailed analysis reports in PDF and DICOM formats

Emphysema Cluster Analysis
Airway Analysis
Pulmonary Vascular Analysis

Linux server (containerized), NVIDIA GPU recommended (CUDA), DICOM network connectivity, web browser client

FDA clearance
CE mark
MFDS (Korea)
PMDA (Japan)
TGA (Australia)
HSA (Singapore)
ANVISA (Brazil)
Health Canada
GDPR

FDA 510(k)
CE (MDR)
MFDS
PMDA
TFDA
TGA
HSA
ANVISA
Health Canada

User authentication / 2FA support (where deployed)

BAA / data processing agreements available (for US customers)

Multi-region/cloud hosting options for major regions (examples: US, EU, Republic of Korea, Australia); customer region choice available depending on deployment


Summary: AVIEW Lung Texture is an AI-powered software by Coreline Soft that analyzes CT scans to detect and quantify patterns associated with interstitial lung diseases (ILD).

AVIEW Lung Texture utilizes artificial intelligence to automatically detect and analyze six patterns indicative of interstitial lung diseases in CT images, providing quantitative assessments to assist radiologists in diagnosis and monitoring disease progression.

radiologists
pulmonologists
medical imaging professionals

South Korea
United States
Europe
Japan
Taiwan
Singapore
Australia
Brazil

South Korea
United States
Germany
Italy
Japan
Taiwan
Singapore
Australia
Brazil

Quantitative fibrosis and normal lung metrics (CT-Fib%, CT-Norm%)

Lobe-based segmentation and visualization

Bull's eye charts and tabular/CSV export of results

Automatic report generation (structured diagnostic report)

Pattern comparison and manual modification of segmentation

Multi-layout image viewer with zoom and overlay

Content-based image retrieval (CBIR) for similar-case retrieval

Real-time comparison between analyzed pattern and original CT

Support for thin-section chest CT analysis

aview ILA module (Interstitial Lung Abnormalities)

aview Pseudonymization Server (de-identification)

Hospital information systems / RIS (via standard interfaces)

Windows Server; DICOM network connectivity; GPU recommended for AI processing; sufficient CPU/RAM and disk for CT volumes

MFDS (Korea)
CE (Europe)
TGA (Australia)
HSA (Singapore)
ANVISA (Brazil)
Health Canada (HC)

FDA 510(k) clearance K214036
CE (MDR)
MFDS (Korea)
PMDA (Japan)
TGA (Australia)
HSA (Singapore)
ANVISA (Brazil)
Health Canada (HC)

Role-based access control (RBAC)
Audit logging
Encryption in transit

Pseudonymization / de-identification server available

Region-specific hosting options (Korea, EU, North America) available depending on deployment


Summary: NeuroQuant MS is an AI-driven software by Cortechs.ai that automates the detection, quantification, and tracking of multiple sclerosis (MS) lesions in brain MRI scans, enhancing diagnostic precision and monitoring of disease progression.

NeuroQuant MS utilizes advanced AI algorithms to segment and analyze MS lesions, providing color-coded visualizations and quantitative data on lesion volume changes over time. It integrates seamlessly into radiology workflows, offering reports that assist clinicians in assessing disease activity and treatment response. The software supports the identification of new, stable, shrinking, and enlarging lesions, aiding in personalized patient care. As of January 1, 2024, NeuroQuant MS is eligible for reimbursement under Category III CPT codes 0865T and 0866T for AI-assisted quantitative brain MRI analysis.

radiologists
neurologists
neuroimaging specialists
clinicians
healthcare providers

Neurology
Radiology
Neuroimaging
Multiple Sclerosis

United States
Canada
Europe
Asia
Australia
South America
Africa
Middle East
North America
Global

English Spanish French German Italian Portuguese Dutch Russian Chinese Japanese

United States
Canada
Germany
United Kingdom
India
Australia
Brazil
South Africa
Japan
China

Longitudinal tracking of lesion progression

Automated labeling of new, stable, shrinking, and enlarging lesions

Age-independent analysis using Dynamic Atlas™ technology

Customizable reporting with pre-populated data

Integration with PowerScribe 360 for streamlined reporting

High-accuracy segmentation DICOM overlays

Modifiable contour DICOM-compatible objects (RT-Struct)

Enhanced segmentation with hybrid ML/DL models

Support for multiple sclerosis lesion analysis

Pre- and post-operative 3D volume analysis of brain tumors

Segmentation and longitudinal tracking of FLAIR, T2*GRE, and SWI lesions

Automated tracer activity quantification in PET scans

Automated CT alignment for fast, accurate diagnosis

NeuroQuant® Brain Tumor
NeuroQuant® ARIA
NeuroQuant® PET
NeuroAlign CT
OnQ™ Prostate

PowerScribe 360
PACS
DICOM-compliant PACS viewers
Third-party workstations

CT scanner, MRI scanner, DICOM-compliant PACS

HIPAA
HITRUST CSF
ISO 27001
SOC 1
SOC 2
SOC 3
GDPR

FDA 510(k)
CE/MDR
ONC
ISO 27001
SOC 1
SOC 2
SOC 3
HITRUST CSF

Password authentication with complexity rules

Three-factor authentication for data center access

Continuous monitoring by network operations personnel

Mobile device management (MDM) for corporate devices

Phishing-resistant multi-factor authentication (MFA)

Business Associate Agreement (BAA) available

Employee HIPAA security and privacy training


Summary: OnQ Prostate is an FDA-cleared software solution that enhances prostate MRI imaging using Restriction Spectrum Imaging (RSI) to improve detection, characterization, and localization of clinically significant cancer.

OnQ Prostate leverages RSI, a patented diffusion MRI method, to provide clear, easy-to-interpret images that support collaborative decision-making and enhance targeting for biopsy and therapy. It aims to improve tumor conspicuity, differentiate tumors from non-tumor tissues, and strengthen histopathology correlation based on Gleason Score.

radiologists
urologists
oncologists
medical imaging professionals

Integration in standard reading environment (PACS)

Integration via AI marketplace or distribution platform

PACS
AI marketplace
distribution platform

HIPAA
FDA 510(k) cleared
CE Certification
SOC 2
ISO 27001

BAA available
consent management
anonymization
data minimization

email phone chat ticketing community 24x7

documentation webinars live_online onsite certification


Summary: cvi42 for Cardiac MRI is an advanced imaging software by Circle Cardiovascular Imaging that provides comprehensive, AI-driven analysis for cardiac MRI studies, enhancing diagnostic accuracy and workflow efficiency.

cvi42 for Cardiac MRI offers a suite of tools for cardiac MRI analysis, including function assessment, flow quantification, tissue characterization, and angiography. It utilizes AI-based contouring for accurate and reproducible volumetric assessments of all cardiac chambers, enabling rapid detection of wall motion abnormalities, stroke volume, and ejection fraction. The software also supports quantitative perfusion analysis, aiding in the evaluation of myocardial blood flow and tissue viability. Designed for seamless integration into existing clinical workflows, cvi42 enhances productivity and decision-making in cardiac imaging.

clinicians
radiologists
cardiologists
medical imaging technicians

Cardiology
Radiology
Cardiac Imaging
Medical Imaging

United States
Canada
United Kingdom
Germany
France
Italy
Spain
Australia
Japan
South Korea
China
India
Brazil
Mexico
South Africa
Russia
Saudi Arabia
United Arab Emirates
Singapore

English Spanish French German Italian Portuguese Dutch Japanese Chinese Korean Arabic Russian Hindi Bengali Punjabi Telugu Marathi Tamil Gujarati Malayalam

AI-enabled coronary lumen and wall segmentation

Automated coronary centerline segmentation

Left and right ventricular segmentation (3D)

Automated calcium scoring with AI segmentation

AI-enabled plaque quantification (volume, composition, burden)

Automated stenosis assessment (lesion- and vessel-level)

MPR and CMPR visualizations and 3D heart views

Manual editing tools (contour/centerline editing, AutoFOV)

Structured/customizable reporting (cvi42 | Report)

Web Viewer for image review and report editing in browser

Automated workflows and server-side job queueing

Per-lesion remodeling index and high-risk plaque metrics

Percentile risk display for calcium (MESA-based)

cvi42 | Report
cvi42 | Strain
cvi42 | 4D Flow
cvi42 | Quantitative Perfusion
cvi42 | Mitral Valve
cvi42 | Plaque
cvi42 | CORE CT
cvi42 | Web Viewer
cvi42 | TruPlan
cvi42 | Standard Reporting

Referring physician web access (Web Viewer)

TLS encryption
Encrypted LDAP/AD authentication
Audit logs
2FA
DLP

BAA available
Consent management
Anonymization
Data minimization

On-premise hosting; cloud hosting with region options (US/EU) or hybrid deployments


Summary: DeepHealth Prostate is an AI-powered software solution designed to enhance the efficiency and accuracy of prostate cancer diagnosis by assisting radiologists in interpreting MRI images and integrating seamlessly with various fusion biopsy platforms.

DeepHealth Prostate leverages advanced artificial intelligence to streamline the prostate cancer diagnostic workflow, elevating non-expert radiologists to expert-level performance. It integrates with most fusion biopsy platforms, providing real-time analysis, 3D rendered images of prostate lesions, and bi-parametric guidance on prostate volume and PSA density. The solution has demonstrated a 27% reduction in lesion identification time and improved biopsy sensitivity from 92% to 97%. Additionally, it supports both hosted and on-cloud deployments, offering flexibility in implementation.

United States
Europe
Asia
Australia
Canada

English Spanish French German Italian Dutch Chinese Japanese Korean Arabic

United States
Netherlands
France
Germany
United Kingdom
China
Japan
South Korea
Australia
Canada

Kinetic curve representation per ROI and full prostate gland

3D rendered key images of prostate lesions

Integration with leading fusion biopsy systems

Enhanced diagnostic accuracy
Streamlined reporting process

Koelis 3D Prostate Suite
MIM Symphony
Surgical BioBot Uro Fusion
Esaote MyLab X9 Fusion
Focal Healthcare
Medcom BiopSee
Navigo
Focalyx
BioJet
Exact Imaging

Major OS/DB/hardware needs, or empty if SaaS-only

Encryption
RBAC
SSO/SAML
audit logs
2FA
DLP

BAA available
consent mgmt
anonymization
data minimization


Summary: DeepHealth Lung Check is an AI-powered solution that assists radiologists in detecting, classifying, and tracking the growth of pulmonary nodules, enhancing efficiency and accuracy in lung cancer diagnosis.

DeepHealth Lung Check integrates seamlessly into existing Picture Archiving and Communication Systems (PACS), offering both onsite and cloud deployment options. It automates the detection, classification, quantification, and growth assessment of pulmonary nodules, identifying solid and sub-solid nodules ranging from 3 to 30mm with 95% sensitivity and no more than two false positives per scan. The system provides accurate measurements of nodule diameters and volumes, and can automatically retrieve prior scans to calculate growth percentage and volume doubling time. It is widely adopted across nearly 100 locations in the UK and EU, including 41 out of 45 sites in the UK’s Targeted Lung Health Checks program, processing over 50,000 scans monthly and delivering standardized, customizable, and shareable lung nodule reports to support efficient clinical workflows.

United States
United Kingdom
Netherlands
Germany
France
Italy
Spain
Belgium
Sweden
Norway

AI-powered nodule detection
Nodule classification
Volume quantification
Growth assessment
Integration with PACS
Automated reporting
Prior study retrieval
Standardized reporting
Customizable reporting
Shareable reporting

Lung nodule tracking
Advanced visualization tools

PACS
Nuance PIN
Incepto
Sectra
deepcOS
Blackford
Nordic Medtech
Inobe

Dedicated hardware, Virtual machine, Docker, Cloud-based


Summary: TRACE4AD is an AI-powered medical device that predicts the risk of Alzheimer's disease dementia within 24 months by analyzing brain MRI scans and cognitive measures.

TRACE4AD is a CE-cleared medical device developed by DeepTrace Technologies, utilizing machine learning to analyze brain MRI images and cognitive assessments to predict the risk of Alzheimer's disease dementia within 24 months. It identifies features of brain atrophy associated with early stages of Alzheimer's and provides volume measurements to aid in disease categorization and tracking progression.

AI-powered risk assessment for Alzheimer's disease dementia

Identification of brain atrophy features associated with Alzheimer's

Volume measurements from T1-weighted MRI studies

Integration with cognitive measures for comprehensive assessment

Sensitivity >85%, specificity >80%, PPV >82%, NPV >85%

BAA available
Consent management
Data anonymization


Summary: TRACE4OC is an AI-powered medical device that assesses women's risk of ovarian cancer by analyzing ultrasound images of adnexal masses combined with CA-125 serum levels and menopausal status.

TRACE4OC is a CE-cleared medical device developed by DeepTrace Technologies. It utilizes machine learning to analyze transvaginal ultrasound images of adnexal masses, integrating CA-125 serum levels and menopausal status to classify women's risk of ovarian cancer as very low or medium-high. This tool aids gynecology specialists in the diagnostic process, providing automated reports to support clinical decision-making.

gynecology specialists
radiologists
clinicians

Europe
United States
Canada
Australia
Japan
South Korea
China
India
Brazil
Mexico
South Africa
Russia
Saudi Arabia
United Arab Emirates
Turkey
Egypt
Argentina
Chile
Colombia
Peru

English Italian German French Spanish Portuguese Dutch Russian Chinese Japanese Korean Arabic Turkish Hindi Bengali Punjabi Gujarati Tamil Telugu Marathi Urdu

Italy
United States
Germany
France
United Kingdom
Spain
Netherlands
Switzerland
Belgium
Austria

AI-based analysis of transvaginal ultrasound images

Risk classification of ovarian cancer (very low risk or medium-high risk)

Consideration of menopausal status (pre- or post-menopausal)

Semi-automatic reading of ovarian masses

CA-125 serum levels
Menopausal status data

Windows or Linux server, dedicated hardware

Data encryption
Access control
Audit logs


Summary: CAD4COVID-XRay is an AI-driven software developed by Delft Imaging to assist in the detection and monitoring of COVID-19 through chest X-ray analysis, providing rapid triage support in resource-constrained settings.

CAD4COVID-XRay utilizes deep learning algorithms to analyze chest X-rays, identifying abnormalities indicative of COVID-19. It offers features such as abnormality heatmaps, pathology quantification, and risk scoring, aiding healthcare professionals in efficient patient triage and monitoring. The software is CE certified and has been deployed in over 20 countries, including South Africa and Ghana, to enhance COVID-19 detection and management. It is available free of charge to support global public health efforts during the pandemic.

Pulmonology
Infectious Diseases
Radiology

South Africa
Ghana
Netherlands
United States
India
Indonesia
Philippines
Brazil
Mexico
Nigeria
Kenya
Uganda
Tanzania
Ethiopia
Pakistan
Bangladesh
Vietnam
Thailand
Egypt
Morocco

English Afrikaans Dutch French Spanish Portuguese Arabic Hindi Bengali Vietnamese Thai Swahili Amharic Urdu Filipino Indonesian Turkish Persian Punjabi Tamil

Netherlands
South Africa
United States
India
Indonesia
Philippines
Brazil
Mexico
Nigeria
Kenya
Uganda
Tanzania
Ethiopia
Pakistan
Bangladesh
Vietnam
Thailand
Egypt
Morocco

AI analysis of frontal chest X-rays for COVID-19 detection

Risk scoring (0-100) indicating likelihood of COVID-19

Segmentation overlay highlighting affected lung areas

Fast processing time (3-10 seconds per image)

Cloud-based deployment with local storage options

Offline processing capability (CAD4COVIDbox)

CAD4TB (tuberculosis detection)
CAD4Silicosis (silicosis detection)
Platform analytics/insights module

National TB platforms/programs (via API)

DICOM images; CAD4COVIDbox: on-site workstation with local storage and 6-hour battery; CAD4COVIDcloud: internet connection and web browser

Local data storage for offline deployments

Data synchronization to central cloud (configurable)

Role-based privileges/administrator higher privileges

Audit/logging (platform insights and reporting)

Data processed for analyzing COVID-19 cases

Data used for product development with explicit approval

Offline option stores images and patient data locally (country-level); cloud option synchronizes to Delft cloud (hosting region options not specified)

5 clinical customers in 5 countries
60 research/test users

No user reviews found on Reddit or third-party directories.

No ratings found on third-party directories.

PACS systems
AI marketplaces
distribution platforms


Summary: CAD4TB is an AI-driven software developed by Delft Imaging to assist in the detection and triage of tuberculosis through chest X-ray analysis.

CAD4TB analyzes posterior-anterior chest X-rays to provide image quality assessments, heatmaps highlighting potential abnormalities, and a risk score indicating the likelihood of tuberculosis. It integrates with standard reading environments, operates in offline, cloud-based, or hybrid modes, and processes images within 3 to 10 seconds. The software is CE-certified (Class IIb, MDR) and has been implemented in over 30 countries, supporting more than 10 clinical customers and 40 research/test users. It operates on a pay-per-use pricing model based on the number of analyses conducted.

enterprise
public health programs
government
non-profit/global health

radiologists
clinicians
radiographers/technicians
TB programme managers
screening teams/public health workers

Chest Radiology
Pulmonology
Infectious Diseases (tuberculosis)
Public Health/screening

English Spanish French Portuguese Arabic Russian Chinese Hindi Bengali Urdu Indonesian Tagalog Vietnamese Thai Turkish Persian Swahili Amharic Hausa Yoruba Igbo

Pricing based on the number of analyses conducted; contact vendor for specific rates.

Netherlands
Ghana
South Africa
India
Indonesia
Pakistan
Bangladesh
Philippines
Nigeria
Uganda

AI-powered tuberculosis detection
Rapid analysis (within 5 seconds)
Heatmap highlighting abnormalities
Cardiothoracic ratio evaluation
Offline and online deployment options
Multi-lingual support
Integration with PACS systems

Data encryption
Role-based access control
Audit logs

Data stored locally in offline mode; cloud storage in online mode


Summary: intelliMammo is an AI-driven platform by Densitas that enhances mammography quality, streamlines workflows, and supports early breast cancer detection through automated assessments and advanced analytics.

intelliMammo is a comprehensive AI-powered platform designed to improve mammography quality and operational efficiency. It includes intelliMammo densityAI for standardized breast density assessments, intelliMammo qualityAI for image quality evaluations, and intelliMammo riskVue for breast cancer risk assessments. The platform integrates seamlessly with existing clinical workflows, providing on-demand actionable insights to technologists, radiologists, and administrators. It also offers advanced analytics for benchmarking, monitoring, and trend detection, facilitating continuous quality improvement and compliance with FDA MQSA EQUIP and ACR standards. Additionally, intelliMammo collaborates with partners like CancerIQ to enhance patient adherence and lifetime risk assessments, and with MTMI to provide educational content for technologists, further elevating mammography practices.

clinicians nurses patients admins payers

United States
Canada
Europe
Australia
Asia

Canada
United States
United Kingdom
Germany
France

Automated breast density assessment (ACR BI-RADS alignment)

Mammography positioning quality analysis (positioning error detection)

Image quality metrics (compression, exposure, positioning criteria)

Population and facility-level analytics dashboards

Retrospective audit of archived DICOM studies

Closed-loop traceability and corrective action tracking

Automated EQUIP/MQSA and CAR MAP reporting

Patient-specific risk scorecard / risk assessment

Interactive filtering for clinic/system performance monitoring

Performance indicators for technologists and devices

Compression force and root-cause analysis by vendor/clinic

intelliMammo densityai
intelliMammo qualityai
Analytics / advanced reporting
intelliMaven (GPT AI assistant)

PACS
RIS
Breast imaging reporting systems
Vendor neutral archive (VNA)
Third-party AI platforms
Radiology worklist systems
Intelerad (IntelePACS)
PenRad
MTMI
Blackford Analysis
iCAD
TungstenQI
RAD-AID International

Web browser; DICOM feed or PACS connectivity; internet connection (SaaS) or server installation for on-prem deployments

HIPAA
PIPEDA
MQSA / EQUIP
ACR / CAR MAP alignment

TLS encryption in transit
Data encryption at rest
Role-based access control (RBAC)
Audit logging
SSO/SAML

United States, Canada, United Kingdom (regional hosting options)


Summary: LVivo Toolbox by DiA Imaging Analysis is an AI-powered ultrasound analysis suite designed to automate image acquisition and analysis, enhancing efficiency and accuracy for clinicians of varying experience levels.

LVivo Toolbox offers a comprehensive suite of AI-driven ultrasound analysis tools, including LVivo EF for automatic ejection fraction measurement, LVivo Strain for strain analysis, LVivo SWM for biplane wall motion abnormalities analysis, and LVivo SAX for parasternal short axis view analysis. These tools aim to streamline ultrasound workflows, reduce variability, and improve patient care by providing objective and automated results.

Web
Embedded (ultrasound device)
Windows

Automated ejection fraction (EF) quantification

Left ventricle global and segmental longitudinal strain

Left ventricle segmental wall motion analysis

Right ventricle size and function assessment

Automatic view selection from 2D DICOM clips

Real-time image quality feedback (LVivo IQS)

LVivo IQS (image quality scoring/feedback)

GE Healthcare
Philips Healthcare
Konica Minolta (Exa Cardio PACS)
Change Healthcare
Circle CVI
Edan
Esaote / Ebit
IBM Imaging AI Orchestrator
Neusoft
Terason
Intelerad
Ebit
Sonoscape
Intel

DICOM
DICOM Secondary Capture
HL7 v2
FHIR

Supports DICOM input; available cloud-hosted or on dedicated on-premise hardware for Windows-based PACS integration

CE (MDD Class IIa)
FDA 510(k) (Class II)

User authentication / single sign-on (via integrations)

De-identified output / DICOM secondary capture option

Cloud-hosted with on-premises deployment option; deployed in ~20 countries (regional hosting/on-prem available)


Summary: TIRESYA is Digitec's AI-powered platform enhancing digital radiology through advanced image processing algorithms.

TIRESYA is an artificial intelligence platform developed by Digitec to enhance digital radiology. It integrates advanced image processing algorithms into X-ray systems, improving the acquisition, processing, and management of medical images. Key features include Bone Suppression, Super Zoom, Anatomical Window Level (W/L), Anatomical Automatic Brightness Control (ABC), and Anatomical Exposure Index. TIRESYA is integrated into Digitec's radiology products such as ERACLE, ODIS, and TESEO, and is certified as a Class IIb medical device under the EU Medical Device Regulation (MDR 2017/745).

clinicians
radiologists
medical imaging technicians

Musculoskeletal Radiology
Chest Radiology

Italy
European Union
United States
Canada
Australia
Japan
South Korea
Brazil
India
China
South Africa
Mexico
Russia
United Kingdom
France
Germany
Spain
Netherlands
Sweden
Norway
Denmark

Italy
United States
Germany
France
United Kingdom
Spain
Netherlands
Sweden
Norway
Denmark

Human digital radiography and fluoroscopy acquisition

Encryption
RBAC
SSO/SAML
Audit logs
2FA
DLP


Summary: BoneAge is an AI-powered solution by Gleamer that automates bone age assessment using the Greulich & Pyle atlas method, enhancing precision and consistency in pediatric evaluations.

BoneAge leverages artificial intelligence to automate bone age assessments, reducing inter- and intra-reader variability. It integrates seamlessly into existing radiology workflows, providing rapid and accurate evaluations based on the Greulich & Pyle method. Clinical studies have demonstrated its outstanding accuracy compared to pediatric radiologists' gold standards. The solution is CE-certified and has been deployed in over 80 clinical institutions across more than 15 countries, with plans for further international expansion. It is available through various distribution channels, including AGFA, Aidoc, Blackford, deepc OS, Incepto, and Sectra. BoneAge operates on standard reading environments such as PACS and RIS, with processing times ranging from 1 to 10 minutes per analysis. The pricing model is subscription-based, with fees determined by the number of analyses conducted. The company, Gleamer, was founded in 2017 and has offices in France and the United States.

Clinicians
Pediatricians
Radiologists
Orthopedic Surgeons
Emergency Physicians

Pediatrics
Orthopedics
Endocrinology
Sports Medicine
Clinical Trials

France
United States
Germany
Spain
Italy
United Kingdom
Netherlands
Belgium
Switzerland
Austria
Portugal
Greece
Turkey
United Arab Emirates
Japan
South Korea
Australia
Canada
Mexico
Brazil

English French German Spanish Italian Dutch Portuguese Arabic Japanese Korean Chinese Russian Turkish Greek Ukrainian Polish Czech Hungarian Romanian Bulgarian

Bone age assessment
Fracture detection
Clinical validation studies
Seamless workflow integration
AI-powered interpretation
X-ray analysis
Pelvic and hip fracture detection
Greulich & Pyle method application
Radiology support
Clinical decision support
Automated image analysis
Diagnostic assistance
Patient data security
Regulatory compliance
Clinical study recognition
Scientific publications
Peer-reviewed research
Medical imaging support
Healthcare AI solutions
Radiology AI applications

BoneMetrics
ChestView
BoneView US
BoneView BoneAge
BoneView ChestView
BoneView BoneMetrics
BoneView AI Copilot
BoneView X-ray interpretation
BoneView fracture detection
BoneView clinical validation

Radiology information system integration

DICOM
HL7
FHIR
ICD-10
SNOMED CT
LOINC
CPT
ICD-9
HL7 CDA
HL7 CCD

Encryption
RBAC
SSO/SAML
Audit logs
2FA
DLP
Data masking
Access controls
Data integrity checks
Secure data storage

BAA available
Consent management
Anonymization
Data minimization
Data retention policies
Data access controls
Data sharing policies
Data subject rights management
Data breach notification
Data protection impact assessments


Summary: BoneMetrics is an AI-powered software by Gleamer that automates musculoskeletal measurements on X-ray and EOS images, enhancing precision and workflow efficiency for clinicians.

BoneMetrics utilizes machine learning algorithms to provide automated measurements of the spine, pelvis, feet, and legs, assisting healthcare professionals in evaluating spinal deformities, leg length discrepancies, and other musculoskeletal conditions. It integrates seamlessly with existing imaging systems, offering quantitative angle measurements that support clinical decision-making and improve workflow efficiency and consistency.

Clinicians
Radiologists
Orthopedic Surgeons
Emergency Physicians
Rheumatologists
Family Physicians
Physician Assistants

Orthopedics
Radiology
Emergency Medicine
Rheumatology
Family Medicine

United States
France
Germany
Italy
Spain
United Kingdom
Canada
Australia
Japan
South Korea
China
India
Brazil
Mexico
South Africa
Saudi Arabia
United Arab Emirates
Egypt
Russia
Turkey

English French German Italian Spanish Portuguese Dutch Japanese Korean Chinese Hindi Arabic Russian Turkish Polish Swedish Norwegian Danish Finnish Czech

France
United States
Germany
Italy
Spain
United Kingdom
Canada
Australia
Japan
South Korea

Automated MSK measurements for spine, pelvis/hip, shoulder, leg, knee, feet

Support for standard X‑ray and EOS acquisitions

Automatic point placement with precise landmarks

Intuitive measurement display and visual overlays

Validated measurement reports for clinicians

Embed results into PACS (DICOM SR / image copy)

Reproducibility and standardization of measurements

Export of measurement report with annotated image

Integration gateway for PACS orchestration

Incepto Gateway (PACS integration/orchestration)

PACS/DICOM viewer; Windows, macOS, or Linux OS; network access to PACS/HIS

Encryption in transit and at rest
Role-based access control (RBAC)
Audit logs
SSO/SAML support

GDPR compliance
Data anonymization options

EU and US hosting/office presence; region options available (EU and US)


Summary: ChestView is an AI-powered solution by Gleamer that assists radiologists in detecting and localizing abnormalities in chest X-rays, enhancing diagnostic accuracy and workflow efficiency.

ChestView leverages advanced artificial intelligence algorithms to automatically detect key radiological findings in chest X-rays, including pneumothorax, pleural effusion, consolidation, nodules, and mediastinal or hilar masses. It integrates seamlessly into existing clinical workflows, providing radiologists with critical insights in seconds and significantly improving diagnostic sensitivity and reducing time-to-diagnosis. The solution has received FDA clearance, marking a significant advancement in AI-assisted radiological diagnostics.

Radiologists
Clinicians
Healthcare Providers

United States
Europe
Asia
Australia
Africa
South America
North America
Middle East
Oceania
Antarctica

English French Spanish German Italian Portuguese Dutch Russian Chinese Japanese Korean Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu Marathi

France
United States
Germany
United Kingdom
Italy
Spain
Netherlands
Belgium
Switzerland
Canada

Detection of pneumothorax, pleural effusion, consolidation, lung nodule, mediastinal mass

Lesion localization with explainable regions of interest / heatmaps

Triage and study prioritization / worklist flagging

Automated alerts/notifications for critical findings

Batch processing / concurrent reading aid

Reporting assistance and structured outputs

Explainability / visual overlays for clinician interpretation

Clinical evidence and performance reporting

PACS (vendor-agnostic DICOM integration)

CE (Class IIa)
FDA 510(k) clearance
GDPR

US and EU deployment options (cloud/region choices)

ChestView has significantly improved our detection of urgent and cancerous chest findings, enhancing patient care.


Summary: Breast-SlimView is an AI-driven clinical decision support system for 2D and 3D mammography, designed to assist radiologists in detecting breast cancer by highlighting potentially suspicious areas and reducing diagnostic time.

Breast-SlimView is a patented clinical decision support software developed by Hera-MI for 2D and 3D mammography. Utilizing artificial intelligence, it automatically detects and removes normal physiological areas from mammography images, replacing them with artificial fat, thereby emphasizing potentially suspicious regions. This process, known as 'negativation,' aids radiologists in focusing on critical areas, enhancing diagnostic efficiency and accuracy. The software is CE certified and has been marketed in Europe since February 2020. Hera-MI has initiated the FDA approval process to expand its availability to the United States. The company is also exploring partnerships in the Middle East and other regions to broaden its market presence. Additionally, Breast-SlimView has been referenced on the ANAP (French National Agency for the Support of the Performance of Health and Medical-Social Institutions) platform, highlighting its recognition in the healthcare sector. The software integrates with standard reading environments (PACS) and can be deployed locally on dedicated hardware or virtualized systems. It processes images within 10 to 60 seconds, providing rapid support to radiologists during diagnostic procedures.

Radiologists
Breast Specialists
Medical Imaging Technicians

Breast Imaging
Radiology
Medical Imaging

United States (FDA approval in progress)

English French Italian Portuguese Russian

Pricing based on number of analyses, installations, and users; contact vendor for specific details.

France
United States
Mexico
Germany
Italy
Portugal
Russia

Automated removal of normal breast tissue (vessels, glandular tissue, fatty tissue, mammary gland)

Replacement of removed tissue with artificial fat

Identification and highlighting of potentially suspicious areas

Integration with standard reading environments (PACS)

Integration via AI marketplace or distribution platform

Standalone third-party application support

Automatic analysis trigger upon image acquisition

On-demand analysis trigger via user input

Processing time between 10 to 60 seconds per image

CE certification as a Class IIa medical device

Mammography Technical Evaluation (MTE) for image quality assessment

PACS
AI marketplace platforms
Third-party applications

Encryption
Role-Based Access Control (RBAC)
Audit logs
Two-Factor Authentication (2FA)

Business Associate Agreement (BAA) availability


Summary: ProFound AI for Digital Breast Tomosynthesis is an AI-driven software developed by iCAD to enhance breast cancer detection in 3D mammography images, improving accuracy and efficiency for radiologists.

ProFound AI for Digital Breast Tomosynthesis is an advanced artificial intelligence solution designed to assist radiologists in interpreting 3D mammography images. It rapidly analyzes each tomosynthesis image, detecting malignant soft tissue densities and calcifications with high accuracy. The software provides lesion and case scores, aiding in clinical decision-making and workflow optimization. Clinically proven benefits include an average 8% increase in sensitivity, a 7.2% reduction in unnecessary patient recalls, and a 52.7% reduction in reading time. ProFound AI is compatible with leading digital breast tomosynthesis systems and has received FDA clearance and CE Mark certification. It is available in various regions, including the United States and Europe, and supports multiple languages. The pricing model is subscription-based, with details available upon request. The company, iCAD, was founded in 2004 and has offices in the United States and Europe.

radiologists
clinicians
medical imaging centers

United States
Europe
Canada
Australia
New Zealand
Japan
South Korea
China
India
Brazil
Mexico
Argentina
Chile
Colombia
Peru
South Africa
Egypt
Saudi Arabia
United Arab Emirates
Israel

English Spanish French German Italian Portuguese Dutch Swedish Norwegian Danish Finnish Russian Chinese Japanese Korean Arabic Hebrew Turkish Hindi Bengali

United States
Germany
France
United Kingdom
Italy
Spain
Canada
Australia
Japan
South Korea

Concurrent-read cancer detection for Digital Breast Tomosynthesis (DBT)

Automated lesion detection and marking (soft tissue densities and calcifications)

Case and lesion-level scoring (ProFound Scorecard)

Short-term (1-2 year) personalized risk scoring (ProFound Risk)

Worklist prioritization and color-coded triage

Reduction in reading time / workflow acceleration

Fewer marks per 3D view to reduce distraction

Breast arterial calcification (BAC) assessment (research module)

Multi-vendor OEM compatibility (2D & 3D)

Integration-ready (PACS/RIS/VNA) workflow hooks

OEM mammography vendors (2D & DBT manufacturers)

Dedicated hardware for on-premises deployment; cloud-based infrastructure for cloud deployment

FDA 510(k) clearance
CE Mark (Class IIa, MDD)

Encryption in transit and at rest
Role-based access control (RBAC)
SSO/SAML support
Audit logging


Summary: icobrain cva is an AI-driven software by icometrix that quantifies stroke lesion volumes and assesses tissue perfusion abnormalities in brain MRI scans, aiding clinicians in stroke evaluation and management.

icobrain cva utilizes artificial intelligence to analyze brain MRI scans, providing quantitative assessments of stroke lesions by measuring Tmax and cerebral blood flow (CBF) abnormalities, evaluating arterial input function (AIF) and venous output function (VOF), and generating perfusion maps to support clinical decision-making in stroke care.

United States
Europe
Canada
Australia
Japan
India
Brazil

English Dutch French German Spanish Italian Portuguese Japanese Chinese Korean

Belgium
United States
Canada
Australia
Japan
India
Brazil

Automated quantitative assessment of tissue perfusion

Reporting of core and perfusion lesion volumes

Quantification of Tmax and CBF abnormalities

PACS
RIS
AI marketplace
distribution platform

CE Class IIa MDR
FDA 510(k) cleared Class II

icobrain cva has significantly improved our stroke assessment accuracy.


Summary: icobrain dm is an AI-driven software by icometrix that aids in early detection and monitoring of dementia and Alzheimer's disease through brain MRI analysis.

icobrain dm supports early detection of dementia markers by comparing whole brain and ventricular volumes to age- and sex-matched healthy controls. It assists in differential diagnosis by providing individual volumes of cortical lobes and hippocampi, reporting percentiles compared to healthy controls. Additionally, it evaluates eligibility for amyloid-targeting treatments by reporting total volume of FLAIR white matter hyperintensities and number of T2* GRE hypointensities.

United States
Europe
Canada
Brazil
Australia
Japan
India

English Dutch French German Spanish Italian Portuguese Japanese Chinese Korean Russian Arabic Hindi Bengali Punjabi Telugu Marathi Tamil Urdu Gujarati

Belgium
United States
France
Italy
Brazil
Australia
Japan
India

Brain atrophy measurement and regional volumes

Stroke lesion and perfusion quantification

Tumor core/resection cavity/edema tracking

Clinical decision support metrics and visualizations

Extended reporting templates/custom templates

Regulatory/security documentation pack (MDS2, CAIQ)

Data processing/privacy agreement templates (DPA/BAA)

PACS
RIS
EMR/EHR
Epic
Cerner
Philips
Siemens Healthineers
GE Healthcare
Sectra
Agfa
Radiology viewers
Billing systems (for CPT processing)
Clinical registries/research platforms

icobridge appliance (on-prem Linux-based gateway) or icometrix cloud; DICOM-capable scanners/PACS; hospital network connectivity

FDA cleared (multiple solutions)
CE marked
ISO certified

Data encryption at rest and in transit
Role-based access control (RBAC)
Single sign-on/SAML
Audit logging and traceability
Vulnerability reporting process

US and EU hosting options (regional cloud hosting available)


Summary: icobrain ep is an AI-powered software developed by icometrix to assist in diagnosing and monitoring intractable epilepsy by analyzing hippocampal volumes and asymmetry in brain MRI scans.

icobrain ep aids physicians in detecting hippocampal sclerosis, a common cause of intractable epilepsy, by assessing hippocampal asymmetry and identifying juxtacortical abnormalities. It compares hippocampal asymmetry to age- and sex-matched healthy populations and evaluates FLAIR hyperintensities adjacent to the cortex, which may indicate cortical malformations.

United States
European Union
Canada
Australia
Japan
South Korea
Brazil
India
China
South Africa
Mexico
Russia
Argentina
Saudi Arabia
Turkey
United Arab Emirates
Singapore
Malaysia
Thailand
Indonesia

English Dutch French German Spanish Italian Portuguese Chinese Japanese Korean Russian Arabic Hindi Bengali Punjabi Telugu Marathi Tamil Urdu Gujarati

Belgium
United States
United Kingdom
Germany
France
Netherlands
Italy
Spain
Sweden
Switzerland

FLAIR scan evaluation for cortical dysplasia

HIPAA
GDPR
HITECH
ISO 27001
ISO 13485
MDSAP

Encryption in transit and at rest
Pseudonymization
Role-based access control (RBAC)
Audit logs
SSO/SAML support
Secure on-prem gateway (icobridge)

Cloud hosting with region options (US and EU); on-prem hosting via icobridge for local data retention


Summary: icobrain ms is an AI-driven software solution that analyzes brain MRI scans to monitor multiple sclerosis progression and treatment efficacy.

icobrain ms provides quantitative analysis of multiple sclerosis by assessing changes in FLAIR and T1 lesions, as well as brain volume over time, comparing these metrics to age- and sex-matched healthy individuals. The software aids in detecting disease activity, tracking treatment response, and evaluating disease progression. An advanced version, icobrain ms+, offers additional capabilities for research purposes, including evaluation of the central vein sign and paramagnetic rim lesions based on susceptibility-weighted imaging, as well as analysis of cervical spinal cord cross-sectional surface area from T1-weighted images. The platform is FDA-cleared and CE-marked, ensuring regulatory compliance and clinical validation. It is integrated into over 330 hospitals across 50 countries, supporting clinicians in making informed decisions for patients with multiple sclerosis. The software has demonstrated significant improvements in clinical outcomes, including a 150% increase in disease activity detection, a 2.5x faster detection of treatment failure, and a 68% improvement in outcomes when used alongside drug treatments. Additionally, icobrain ms has been recognized with the ACR Transparent AI badge, highlighting its commitment to transparency and trust in AI applications for neuroimaging. The company, icometrix, was founded in 2011 and is headquartered in Leuven, Belgium, with offices in the United States and other countries. It has been recognized for its innovative contributions to healthcare technology, including being selected for the MedTech Innovator’s 2025 Accelerator Mid-Stage Program. The company has also entered into strategic partnerships, such as with SEQSTER, to enhance neurological care through integrated data solutions. In September 2025, GE HealthCare announced its intent to acquire icometrix, aiming to strengthen its neurology portfolio with advanced brain MRI assessment solutions.

clinicians radiologists neurologists patients admins payers

Neurology
Radiology
Multiple Sclerosis
Neuroimaging
Neurodegenerative Diseases

United States
Belgium
Canada
Brazil
Australia
Japan
India
France
Italy
United Kingdom
Germany
Netherlands
Spain
Sweden
Norway
Denmark
Finland
Switzerland
Austria
Poland

Belgium
United States
France
Italy
Brazil
Australia
Japan
India
United Kingdom
Germany

HIPAA
GDPR
HITECH
ISO 27001
ISO 13485
SOC 2

FDA clearance
CE mark (NB1639)
ISO 13485
ISO 27001
MDSAP


Summary: icobrain tbi is an AI-driven software by icometrix that quantifies brain CT and MRI scans to assess and monitor traumatic brain injury (TBI).

icobrain tbi utilizes deep learning algorithms to analyze CT and MRI brain scans, providing quantitative metrics for acute and sub-acute TBI assessments. It reports on hyperdense volumes, cisternal compression, midline shift, and subtle anomalies in brain volume and inflammation, aiding clinicians in monitoring disease progression and treatment effects. The software is FDA-cleared and CE-marked, integrating seamlessly into clinical workflows to enhance precision and personalized care in neurology.

clinicians
radiologists
neurologists
neurosurgeons
medical researchers

Neurology
Neurosurgery
Radiology
Trauma Care
Emergency Medicine

United States
Europe
Canada
Australia
Brazil
Japan

English Dutch French German Spanish Italian Portuguese Japanese

icobrain MS (multiple sclerosis analytics)

PACS
RIS
EMR/EHR
Epic
Cerner
Philips
Siemens Healthineers
GE Healthcare
Sectra
Agfa
Radiology viewers
Billing systems
Clinical registries
Research platforms

HIPAA
GDPR
HITECH
ISO 13485
ISO 27001
MDSAP

Data encryption at rest and in transit
Role-based access control (RBAC)
Single sign-on (SSO)/SAML
Audit logging and traceability
Vulnerability reporting process

US and EU hosting options; on-prem hosting via icobridge for local data retention


Summary: Icolung is a cloud-based AI software developed by icometrix to quantify lung involvement in COVID-19 patients using non-contrast chest CT scans, providing rapid and objective assessments to assist clinicians in patient triage and monitoring.

Icolung is a cloud-based AI software developed by icometrix to quantify lung involvement in COVID-19 patients using non-contrast chest CT scans. It automates the assessment of lesion burden, providing total and regional volumetrics in six pulmonary regions, and quantifies lung pathology per type of CT finding, such as Ground Glass Opacity, Consolidation, and Crazy Paving Pattern. The software integrates seamlessly into hospital PACS, delivering concise reports and annotated images within 10 minutes. Initially launched during the COVID-19 pandemic, Icolung received CE marking for clinical use in Europe on April 23, 2020, and was permitted for clinical use in the U.S. during the public health emergency related to COVID-19. It is currently offered pro bono worldwide. Icolung has been integrated into over 75 clinical practices across 17 countries, supporting clinicians in the rapid assessment and triage of COVID-19 patients. The software is available in English and other languages, with deployment options including integration via AI marketplace or distribution platform. Processing time ranges from 1 to 10 minutes, and it is compatible with standard reading environments (PACS).

clinicians
radiologists
hospital administrators

Pulmonology
Infectious Disease
Radiology

Europe
United States
Canada
Australia
Brazil
India
Japan
South America
Asia
Africa
Middle East
Oceania
North America
South Asia
Southeast Asia
East Asia
Central America
Caribbean
Western Europe
Eastern Europe

English Dutch French German Spanish Italian Portuguese Russian Chinese Japanese Korean Arabic Hindi Bengali Punjabi Telugu Marathi Tamil Urdu Gujarati

Lesion classification
Quantification of lung involvement
Total and lobular

Data encryption at rest and in transit
Role-based access control (RBAC)
Single sign-on (SSO) / SAML
Audit logging and traceability
Vulnerability reporting process


Summary: IB DCE is a software tool that analyzes T1-weighted MRI images to generate perfusion and permeability parameter maps, aiding in tumor assessment and treatment monitoring.

IB DCE processes dynamic contrast-enhanced MRI datasets to produce quantitative maps of parameters such as Ktrans, Ve, Vp, and T10. It employs pharmacokinetic models like Extended Tofts, Tofts, and Patlak for accurate analysis. The software automates the generation of vascular input functions and integrates seamlessly with existing medical imaging systems, facilitating efficient clinical workflows.

radiologists
oncologists
medical physicists
clinical researchers

United States
United Kingdom
European Union
Switzerland

United States
United Kingdom
Switzerland
European Union

Fast generation of perfusion parameter maps (Ktrans, Ve, Vp, T10, Initial Slope, Time to Peak (TTP), Peak Enhancement, initial area under curve (IAUC))

Accurate implementation of the Extended Tofts, Tofts, and Patlak pharmacokinetic models

Automatic generation of Vascular Input Function (VIF)

Automatic selection of flip-angle series to process

Manual override of flip-angle series selection

Normalization of parameters to normal-appearing tissue

Output maps fused to anatomical images with image registration

Simple and intuitive calculation process

Automatic export of new calculated images as DICOM series to PACS

Automatic report generation in the form of a DICOM series

IB Clinic™ integration
IB Rad Tech™ integration
IB Diffusion™ integration
IB Neuro™ integration
IB Delta Suite™ integration

PACS
IB Clinic™
IB Rad Tech™
IB Diffusion™
IB Neuro™
IB Delta Suite™

HIPAA
GDPR
HITECH
SOC 2
ISO 27001
FDA 510(k)
CE Marking
ISO 13485


Summary: IB Delta Suite is a software solution that generates quantitative Delta T1 maps from routine MRI exams to assist in monitoring brain tumor treatment response.

IB Delta Suite automates the creation of Delta T1 maps, providing objective and rapid delineation of contrast-enhancing regions in brain tumors. It integrates seamlessly into standard reading environments, offering both standalone and integrated deployment options. The software is FDA 510(k) cleared and CE certified, ensuring compliance with regulatory standards. It is available through various distribution channels, including Eureka Clinical AI, QMENTA, Blackford Analysis, Medimsight, CorTechs Labs, aycan Medical Systems, Pixmeo, and Calantic. Pricing models include pay-per-use, subscription, and one-off payments with service contracts, based on the number of users, installations, or analyses.

radiologists
neuro-oncologists
MRI technologists
medical imaging professionals

United States
European Union
United Kingdom
Switzerland

Pay-per-use, subscription, one-off payment with service contract; based on number of users, installations, or analyses.

Multiple inter- and intra-study MR registration algorithms (rCBV, dT1, ADC, FTB)

Proprietary image standardization for consistent longitudinal comparisons

Quantitative Delta T1 (qDT1/dT1) map generation from pre/post-contrast T1

Automatic separation of blood products from enhancing tumor

Thresholding to auto-generate tumor regions of interest

One-click calculations with intuitive UI

Automatic export of new images as DICOM series

Push/export processed series and automated report as DICOM to PACS

IB Neuro
IB DCE
IB Diffusion
IB Rad Tech
IB StoneChecker
IB Nimble

PACS (DICOM push)
Aycan workstation
OsiriX (macOS) plugin
Horos
GE Healthcare (reported compatibility)

Workstation installation (OsiriX/Horos plugin or Aycan workstation/Windows workstation); requires DICOM connectivity; (detailed OS/DB/hardware requirements by vendor)

HIPAA
FDA 510(k) cleared, Class II
CE Certified, Class I, MDD

Montgomery Cancer Center (AL)
MD Anderson Cancer Center

Facile à explorer et à naviguer ainsi qu'à utiliser, ils fournissent un retour d'information pour chaque problème qui se présente.

documentation webinars live_online onsite trial

Bayer Pharmaceuticals
Blackford Analysis
Medimsight
TeraRecon
Aycan Medical Systems
CorTechs Labs
Pixmeo
QMENTA


Summary: IB Diffusion is a software tool that analyzes MRI diffusion-weighted images to generate various diffusion parameters, aiding in the early detection and evaluation of brain tumors.

IB Diffusion processes MRI diffusion-weighted images to produce Apparent Diffusion Coefficient (ADC) maps, extrapolated b-values, intravoxel inherent motion (IVIM), and other diffusion parameters. It offers features like direct reading of b-values from DICOM headers, standard two-point ADC calculation, linear regression for ADC maps with multiple b-values, normalization of ADC values using mean ROI values, intuitive processing with manual override, automatic export of calculated images as new DICOM series, and automatic report generation in DICOM format. These capabilities assist clinicians in early detection and assessment of brain tumors, particularly gliomas, by identifying tissue abnormalities before visible anatomical changes occur.

United States
Europe
Asia
Australia
Canada
South America
Africa
Middle East

English Spanish French German Italian Portuguese Dutch Russian Chinese Japanese Korean Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu Marathi

United States
United Kingdom
Germany
France
Italy
Spain
Netherlands
Sweden
Switzerland
Australia

linear regression for multi-b-value ADC maps

intuitive one-click calculations with manual override

automatic export of calculated images as DICOM series

automatic report generation as DICOM series

PACS (DICOM push)
OsiriX (plugin)
Third-party viewers/workstations
TeraRecon (partner integrations)
Qmenta (platform listing)
Cortechs.ai (platform/partner mentions)

DICOM-compatible PACS and compatible viewer/workstation (e.g., OsiriX); server/workstation install


Summary: StoneChecker is a medical software tool that analyzes kidney stones using non-contrast CT scans to assist in clinical decision-making.

StoneChecker is a semi-automated software developed by Imaging Biometrics, designed to provide clinicians with detailed metrics about kidney stones from non-contrast CT scans. Utilizing the TexRAD algorithm, it assesses various physical attributes of renal stones, including volume, mean Hounsfield unit (HU) density, skin-to-stone distance, entropy, kurtosis, and skewness. These metrics have been shown to predict stone-free rates and outcomes of lithotripsy procedures. The software has been available for research use since 2017 and received FDA clearance for marketing in the USA in September 2019. It is also available for commercial use in the European Union and South Korea. StoneChecker has been validated in studies, demonstrating its ability to predict the ease of stone fragmentation during shockwave lithotripsy. The software integrates seamlessly into clinical workflows, providing rapid and accurate assessments to aid in patient management.

clinicians
urologists
radiologists
medical imaging professionals

United States
European Union
South Korea

English Korean German French Spanish Italian Dutch Portuguese Swedish Danish Norwegian Finnish Greek Polish Czech Hungarian Romanian Bulgarian Croatian Slovak

United States
United Kingdom
South Korea
Germany
France
Spain
Italy
Netherlands
Portugal
Sweden

Generation of perfusion parameter maps (Ktrans, Ve, Vp, T10, IAUC, TTP, Peak Enhancement)

Extended Tofts, Tofts, and Patlak pharmacokinetic models

Automatic Vascular Input Function (VIF) generation

Automatic flip-angle series selection with manual override

Normalization to normal-appearing tissue

Image registration and fusion of parametric maps to anatomical images

Automatic export of calculated images as new DICOM series

Automatic report generation as a DICOM series

Designed as platform-independent plugins for existing viewers/workstations

HIPAA Security Rule (for healthcare customers)

GDPR requirements (for EU data protection)

ISO 27001
ISO 13485
OMOP/EHDEN
OWASP Application Security Verification

Audit Logging
Role Based Access Controls
Authentication and Authorization
Data Encryption at Rest
Data Encryption in Motion
Secure SDLC
Annual penetration testing

United States, European Union, Canada, Australia, United Kingdom


Summary: Duali-Q is an AI-driven, cloud-based quality management system for radiology departments, enhancing CT scan analysis to improve detection rates of life-threatening diseases.

Duali-Q by IMedis is a comprehensive quality management system for radiology departments. Utilizing AI, it analyzes CT scans and reports to identify overlooked findings, such as pulmonary nodules and liver lesions, thereby improving diagnostic accuracy and patient outcomes. The system operates independently of existing radiology workflows, minimizing disruption and reducing alert fatigue. Proven to increase detection rates of life-threatening diseases by 13%, Duali-Q is currently in use at leading teaching hospitals in the US, UK, and Israel.

Radiologists
Radiology Administrators
Healthcare Providers

Radiology
Oncology
Cardiology
Pulmonology
Gastroenterology
Vascular Medicine

English Hebrew Spanish French Italian Japanese

Israel
United States
United Kingdom
Japan

Assessment of thoracic and abdominal aorta dilation

ISO 13485
FDA 21 CFR Part 820
CE Class I MDD

Role-based access control
Audit logs
Data encryption


Summary: ARVA is an AI-driven solution that automates aortic diameter and volume measurements from CT scans, enhancing diagnostic accuracy and workflow efficiency.

ARVA, developed by Incepto, is an AI-powered tool designed to automatically measure the maximum transverse diameter and volume of the entire aorta from CT scans. It integrates seamlessly into existing PACS or review workstations, providing structured reports and 3D reconstructions. ARVA is CE-marked as a Class IIa medical device and is compatible with all CT machines, aiming to standardize aortic measurements and improve patient monitoring.

clinicians
radiologists
cardiologists
vascular surgeons
medical imaging professionals

English French German Spanish Italian Portuguese

Fully automatic volumetric analysis of whole aorta

Maximum transverse diameter measurement by aortic section

Aortic volume measurement by section (S1-S7)

Automatic retrieval and comparison of prior exams from PACS

Structured report generation available in PACS/workstation

Longitudinal tracking of diameters and volumes

Key image extraction showing maximum diameters aligned with centerline

Accepts CT DICOM studies; integrates into existing PACS/review workstations; compatible with all CT vendors

CE mark (Class IIa) — Notified Body: IMQ


Summary: KEROS is an AI-driven solution that automates knee MRI analysis, detecting and characterizing various knee pathologies, and generates pre-filled structured reports to enhance diagnostic efficiency.

KEROS is an AI solution for knee MRI diagnosis. It automatically analyzes primary knee anatomical structures, detecting ACL tears, MCL tears, meniscal tears, ligament, menisci, and cartilage lesions, along with identifying bone edema, joint effusions, and popliteal cysts. KEROS also measures patellar height, trochlear dysplasia, and TT-TG, providing comparisons to reference values. It generates schematic reports in SCPT format, which can be integrated with reporting software to pre-fill findings and finalize reports in the RIS. KEROS is CE-marked (Class IIa) and intended for use by clinicians. Processing time typically ranges from 1 to 10 minutes per study.

enterprise
health system
radiology departments

radiologists
orthopaedic surgeons
MSK clinicians
radiology technologists
clinical admins

Europe
United States
Canada
Australia
Japan
South Korea
Brazil
India
China
South Africa
Mexico
Russia
Saudi Arabia
United Arab Emirates
Turkey
Argentina
Chile
Colombia
Peru
Egypt

English French German Spanish Italian Portuguese Dutch Russian Chinese Japanese Korean Arabic Turkish Hindi Bengali Punjabi Urdu Tamil Telugu Marathi

Subscription-based; pricing driven by number of analyses; contact vendor for rates and trial info.

France
Germany
Italy
Luxembourg
Portugal
Spain
Switzerland
Netherlands
United States

Detection and characterization of ACL, MCL, meniscal, and cartilage lesions

Identification of bone edema, joint effusions, and popliteal cysts

Measurement of patellar height, trochlear dysplasia, and TT-TG

Automatic generation of pre-filled structured reports in SCPT format

Comparison of measurements to MRI reference values

PACS
RIS
AI marketplaces
distribution platforms

Data encryption
Role-based access control (RBAC)
Audit logs


Summary: PAROS is an AI-powered radiology solution that automates prostate MRI analysis, enhancing diagnostic accuracy and efficiency for radiologists.

PAROS is an AI-augmented radiology software developed by Incepto Medical, designed to assist radiologists in interpreting prostate MRI scans. It automatically segments the prostate to estimate its volume, detects and segments prostate lesions, and characterizes them using the PI-RADS schema, indicating their level of suspicion. The solution also generates pre-filled reports in 'Secondary Capture' format, integrates seamlessly into standard reading environments like PACS and RIS, and provides overlays of segmented prostate and detected lesions with heatmaps highlighting suspicious areas. PAROS is CE-marked as a Class IIa medical device and is intended to support physicians in diagnosing prostate cancer. It is available in France and other European countries, with plans to expand further. The product is offered on a subscription basis, with pricing details available upon request from the vendor.

radiologists
urologists
oncologists
radiology technicians
clinical administrators

Contact vendor for pricing, licensing, and trial information

Lesion detection, segmentation, and characterization

Report suggestion
Diagnosis verification

PACS
RIS
AI marketplace
Third-party applications


Summary: InferRead CT Pneumonia is an AI-powered diagnostic software that analyzes chest CT scans to detect and assess pneumonia, including COVID-19-related cases, assisting clinicians in early detection and triage.

InferRead CT Pneumonia reads chest CT DICOM images to detect pneumonia lesions, flagging suspected cases in the study list. It provides segmentation, quantification, and analysis of lesion volume and density, with follow-up functions to assess disease progression. The software is intended to assist clinicians and does not replace their interpretation and diagnosis. It is CE marked, NMPA approved, and UKCA marked. Deployment options include on-premise and cloud-based environments, integrating seamlessly into clinical workflows. The system is paired with intuitive tools tailored to the needs of clinicians. The software is intended to be used in a LAN network to prevent the leak of patient data. Users should ensure they have received necessary training provided by Infervision before using the software to prevent misdiagnosis or missed diagnosis. The software is used for computer-aided diagnosis and should not be directly used to generate diagnosis reports to prevent misdiagnosis or missed diagnosis. Users should inform Infervision when misdiagnosis, missed diagnosis, or delay in diagnosis occurs. If any serious incidents occur, they should be reported to Infervision and the competent authority in the user's country in time. If the Patient ID or Patient Name is missing in the system, users should complete the corresponding label and make a diagnosis to avoid mismatch between the patient and the diagnosis result, which could result in misdiagnosis or missed diagnosis. The suspected pneumonia in the study list is only intended to prioritize cases. The final diagnosis depends on the judgment of clinicians. The measurement of the software is based on image measurement, not objective measurement.

clinicians
radiologists
healthcare providers

Pulmonology
Infectious Diseases
Emergency Medicine
Critical Care
Internal Medicine
Family Medicine
Geriatrics
Pediatrics
Cardiology
Oncology
Orthopedics
Neurology
Gastroenterology
Nephrology
Rheumatology
Endocrinology
Hematology
Dermatology
Allergy And Immunology
Psychiatry

United States
European Union
China
United Kingdom
Japan
South Korea
India
Australia
Canada
Brazil
Mexico
South Africa
Russia
Saudi Arabia
United Arab Emirates
Singapore
Malaysia
Thailand
Indonesia
Philippines
Vietnam

English Chinese German French Spanish Italian Portuguese Dutch Russian Japanese Korean Arabic Hindi Bengali Punjabi Telugu Marathi Tamil Urdu Gujarati

China
United States
Germany
France
United Kingdom
Japan
South Korea
India
Australia
Canada

Automated detection of pneumonia lesions in chest CT DICOM images

Segmentation and quantification of lesion volume and density

Follow-up function for assessing disease progression

Prioritization of suspected pneumonia cases in study lists

3D planning/visualization integrations (InferOperate interoperability)

EHR integration (via standard hospital interfaces)

Browser-based client; on-prem server deployment supported (PACS connectivity, DICOM store/SCU), cloud-hosted option available

Role-based access control (RBAC)
Encrypted data in transit (TLS)
Audit logging
SSO/SAML (enterprise SSO integrations)

Anonymization/pseudonymization options for research workflows

Consent-driven data use for research deployments

On-prem deployment or cloud hosting with region choices; supports local (customer) on-prem hosting and cloud multi-region options


Summary: InferRead DR Chest is an AI-powered software developed by Infervision to assist in the detection of multiple chest abnormalities from X-ray images, including tuberculosis, fractures, and pleural effusion.

InferRead DR Chest is a computer-aided diagnostic software designed to analyze chest X-ray images and evaluate the probability of various chest abnormalities, such as tuberculosis, fractures, pleural effusion, and pneumothorax. It integrates with standard reading environments like PACS, RIS, and CIS, and can be deployed locally on dedicated hardware or virtualized environments. The software processes images automatically upon acquisition or on-demand, providing results within 3 to 10 seconds. It is CE marked and intended to assist physicians in diagnosis, not to make diagnoses independently.

radiologists
clinicians
medical imaging professionals

Pulmonology
Thoracic Surgery
Emergency Medicine
Infectious Diseases
Orthopedics

English Chinese Spanish French German Italian Portuguese Russian Japanese Korean Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu Marathi Tamil

China
United States
United Kingdom
Germany
Japan
South Korea
India
Brazil
Russia
Australia

Automated detection of 14 chest pathologies including pneumonia, tuberculosis, fractures, nodules, pleural effusion, and pulmonary infections

Abnormality detection in chest X-ray images

Integration with standard reading environments (PACS)

Integration with Radiology Information Systems (RIS)

Integration with Clinical Information Systems (CIS)

Standalone third-party application support

Standalone web-based application support

Automatic analysis trigger immediately after image acquisition

On-demand analysis triggered by user actions

Processing time of 3–10 seconds per image

PACS
RIS
CIS
Standalone third-party applications
Standalone web-based applications

BAA available for US customers (commercial offering)


Summary: JLK-DWI is an AI-driven software that analyzes diffusion-weighted MRI scans to detect and segment cerebral infarctions, providing lesion size, location, and ischemic stroke subtype estimations.

JLK-DWI utilizes artificial intelligence to process diffusion-weighted MRI images, identifying cerebral infarct lesions and generating heatmaps, lesion segmentations, volumes, and probabilities for major ischemic stroke subtypes, including large artery atherosclerosis, cardioembolic, and small-vessel. Outputs are provided in DICOM format, facilitating integration with PACS systems. The software operates in approximately 3–10 seconds per case, supporting rapid clinical assessment. Deployment options include cloud-based, hybrid, and on-premises solutions. It has received CE (MDD) Class I certification and is commercially licensed. The company, JLK, was founded in 2014 and has offices in South Korea. Notable customers include Samsung Seoul Hospital, Bundang Seoul National University Hospital, and University of Missouri Hospital.

Radiologists
Neuroradiologists
Stroke Neurologists
Radiology Technologists
Hospital IT Administrators

Neurology
Radiology
Emergency Medicine
Stroke Care
Neurosurgery
Rehabilitation Medicine
Internal Medicine
Geriatrics
Cardiology
Endocrinology
Pulmonology
Hematology
Infectious Disease
Oncology
Orthopedics
Ophthalmology
Otolaryngology
Dermatology
Urology
Gastroenterology

South Korea
United States
Japan
Europe
Asia
North America
Australia
New Zealand
Middle East
Africa
South America
Central America
Caribbean
Southeast Asia
East Asia
South Asia
Western Europe
Eastern Europe
Northern Europe
Southern Europe

Korean English Japanese Chinese Spanish French German Italian Portuguese Russian Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu Marathi

cloud-based
hybrid solution
locally on dedicated hardware

ischemic stroke subclassification
lesion detection
heatmap overlay
probability of stroke subtype

stand-alone third party application
stand-alone web-based


JAD-02K is a medical imaging device developed by JLK, designed to enhance diagnostic accuracy and workflow efficiency in healthcare settings. It offers advanced imaging capabilities, user-friendly interface, and seamless integration with existing healthcare systems, aiming to improve patient care and operational productivity.

Radiology
Cardiology
Orthopedics
Neurology
Oncology
Pediatrics
Emergency Medicine
Gastroenterology
Pulmonology
Urology
Obstetrics And Gynecology
Dermatology
Ent
Ophthalmology
Dentistry
Vascular Surgery
Plastic Surgery
Trauma Surgery
Sports Medicine
Internal Medicine

South Korea
United States
Japan
China
Germany
France
United Kingdom
Canada
Australia
India
Brazil
Mexico
Italy
Spain
Russia
South Africa
Saudi Arabia
United Arab Emirates
Singapore
Malaysia

Korean English Japanese Chinese German French Spanish Italian Russian Arabic Portuguese Hindi Bengali Punjabi Telugu Marathi Tamil Gujarati Malay Thai

3D convolutional neural network technology

Perception aid (prompting abnormalities/results/heatmaps)

Stand-alone third-party application
Stand-alone web-based

Dedicated hardware or cloud-based deployment

User authentication
Role-based access control (RBAC)
Audit logs


Summary: JBA-01K is an AI-driven system developed by JLK Inc. for detecting cerebral aneurysms using MR angiography images, assisting healthcare professionals in diagnosis.

JBA-01K is an artificial intelligence system designed to analyze brain MR angiography images to detect cerebral aneurysms. Utilizing 3D convolutional neural network technology, it identifies aneurysm lesions and provides probability assessments based on MR angiography and clinical data, aiding physicians in diagnosis. The system operates as a standalone application, offering features such as perception aid with heatmaps and report suggestions. It processes input formats like DICOM and JPG, delivering location annotations in report format. Deployment options include local installation on dedicated hardware, cloud-based solutions, or hybrid configurations. The analysis is triggered on-demand by user actions like button clicks or image uploads, with processing times ranging from 10 to 60 seconds. JBA-01K has been on the market since September 2019, with distribution in two countries. It is certified as a Class I medical device under the Medical Device Directive (MDD) in Europe but has not yet received FDA approval. The pricing model is pay-per-use or subscription-based, depending on the number of users or installations. The company, JLK Inc., was founded in 2014 and is headquartered in Seoul, Korea.

Clinicians
Radiologists
Neurologists
Medical Staff
Healthcare Professionals

Neurology
Radiology
Neuroimaging
Vascular Medicine
Emergency Medicine
Stroke Care
Neurosurgery
Cardiology
Internal Medicine
Critical Care
Neurovascular Surgery
Neurointervention
Neurodiagnostics
Neurocritical Care
Neurorehabilitation
Neurovascular Imaging
Neurovascular Disease
Neurovascular Diagnostics
Neurovascular Intervention

South Korea
United States
Europe
Asia
Africa
Australia
Canada
Mexico
Brazil
Argentina
Chile
Colombia
Peru
Venezuela
Ecuador
Paraguay
Uruguay
Bolivia
Guyana
Suriname

Korean English Spanish French German Italian Portuguese Dutch Russian Chinese Japanese Arabic Hindi Bengali Punjabi Javanese Turkish Vietnamese Telugu Marathi

South Korea
United States
Germany
France
United Kingdom
Japan
China
India
Brazil
Australia

cloud-based
hybrid
on-prem (dedicated hardware)

Probability scoring for aneurysm lesions

Integration as stand-alone third-party application

Integration as stand-alone web-based application

Encryption
RBAC
SSO/SAML
audit logs
2FA
DLP

Hosting/region options (e.g., EU-only, US/EU regions, BYO cloud region)


Summary: JBD-01K is an AI-driven software that analyzes 2D mammography images to detect and localize breast masses and microcalcifications, generating comprehensive reports to assist radiologists in diagnosis.

JBD-01K, developed by JLK Inc., is an artificial intelligence-based diagnostic tool designed to enhance breast cancer detection. It processes 2D mammography images in DICOM or JPG formats, identifying and localizing breast masses and microcalcifications. The software provides location annotations, probability scores, and generates structured PDF reports. It integrates seamlessly with Picture Archiving and Communication Systems (PACS) and can be deployed in cloud, hybrid, or on-premises environments. The processing time for each image is approximately 3–10 seconds. JBD-01K has been CE marked (MDD Class I) and has been marketed since January 2020. It also holds KFDA/MFDS medical device registration. The software supports DICOM and HL7 v2 data standards and offers an API for integration. It is compatible with Linux (server), Windows (client), and web-based platforms. The pricing model is subscription-based, with costs depending on the number of installations and users; interested parties are advised to contact the vendor for detailed pricing information. The license terms are proprietary. JLK Inc. was founded in 2014 and has offices in South Korea, Japan, and the United States.

radiologists
clinicians
radiology technicians
PACS administrators

South Korea
Japan
United States
Thailand
Vietnam
Indonesia
Turkey
New Zealand
Australia
Europe

Korean
English
Japanese
Thai
Vietnamese
Indonesian
Turkish
New Zealand English
Australian English
European languages

Subscription model; pricing based on number of installations and number of users — contact vendor

AI detection of breast masses on mammography

Integration with PACS/diagnostic viewers

SDK for integration
PACS connector / DICOM gateway
Advanced reporting templates

Server with GPU support (Linux recommended); DICOM network connectivity; SDK for client integration

CE mark
KFDA / MFDS medical device registration

TLS encryption in transit
Role-based access control (RBAC)
Audit logging
User authentication

Support for de-identification/anonymization of DICOM exports

Customer data segregation via on-prem or dedicated deployment

Customer-hosted (on-prem) or vendor-managed cloud options; region selectable by deployment


Summary: JBS-01K is an AI-driven medical system developed by JLK Inc. that analyzes MR images to diagnose ischemic stroke subtypes and detect lesions, aiding clinicians in stroke assessment and classification.

JBS-01K utilizes 3D hybrid artificial neural networks to process MR images—including DWI, FLAIR, T1, and T2 sequences—and clinical data to identify ischemic stroke subtypes and lesions. It provides heatmap overlays and stroke subtype probabilities to assist clinicians in diagnosis and treatment planning.

Locally on dedicated hardware
Cloud-based
Hybrid solution

Lesion detection
Ischemic stroke subclassification
Heatmap overlay
Probability of stroke subtype

PACS (Picture Archiving and Communication System)


JBS-04K is a medical imaging device developed by JLK, designed to enhance diagnostic accuracy and workflow efficiency in healthcare settings. It offers advanced imaging capabilities, user-friendly interface, and seamless integration with existing healthcare systems, aiming to improve patient care and operational productivity.

clinicians
radiologists
medical technicians

Radiology
Cardiology
Orthopedics
Neurology
Oncology
Pediatrics
Gastroenterology
Pulmonology
Urology
Obstetrics
Gynecology
Emergency Medicine
Vascular Surgery
Orthopedic Surgery
Neurosurgery
Cardiothoracic Surgery
Interventional Radiology
Interventional Cardiology
Interventional Oncology
Interventional Pulmonology

United States
Canada
Mexico
United Kingdom
Germany
France
Italy
Spain
Australia
Japan
South Korea
China
India
Brazil
South Africa
Russia
Saudi Arabia
United Arab Emirates
Argentina
Chile

English Spanish French German Italian Portuguese Dutch Russian Chinese Japanese Korean Arabic Hindi Bengali Punjabi Gujarati Tamil Telugu Marathi Urdu

United States
South Korea
Germany
France
United Kingdom
Japan
China
India
Brazil
Australia

Cloud-based
Hybrid solution
Locally on dedicated hardware

Stand-alone third party application
Stand-alone webbased

Triggered by a user through e.g. a button click


JLD - 01K is a radiology imaging device developed by JLK, designed to enhance diagnostic imaging capabilities in medical settings. It offers advanced imaging features to support accurate and efficient medical diagnoses.

South Korea
United States
Europe
Asia
Australia
Canada
Japan
China
India
Brazil
Mexico
South Africa
Russia
United Kingdom
France
Germany
Italy
Spain
Netherlands
Sweden
Norway

Korean English Spanish French German Italian Portuguese Dutch Swedish Norwegian Chinese Japanese Russian Arabic Hindi Bengali Punjabi Telugu Marathi Tamil Gujarati

South Korea
United States
Germany
China
India
Japan
Brazil
Mexico
South Africa
Russia

Automated lung nodule detection in chest CT

Standalone / third-party application (PACS/RIS via DICOM workflows implied)

Accepts DICOM input; deployable cloud-based, hybrid, or on dedicated local hardware


Summary: JPC-01K is an AI-driven medical imaging system that analyzes multiparametric MRI scans to detect and localize prostate cancer, assisting clinicians in diagnosis and targeted biopsy planning.

JPC-01K utilizes artificial neural networks to process multiparametric MRI images—including T2, DWI, and DCE sequences—to identify prostate cancer locations and assess their probability. The system overlays heatmaps on MRI scans, providing clinicians with visual and quantitative data to guide MR-targeted biopsies, thereby reducing patient discomfort and procedural risks. It has received CE certification as a Class I medical device and is in the process of obtaining FDA approval for the U.S. market.

clinicians radiologists urologists patients

South Korea
European Union
United States (pending FDA approval)

South Korea
United States
Japan
Thailand
Vietnam
Indonesia
Turkey
New Zealand
Taiwan
China

Prostate cancer detection
Heatmap overlay
Probability visualization
Report generation

CE Certified, Class I, MDD
FDA clearance


Summary: JLK Inc. offers AI-driven medical imaging solutions for various specialties, enhancing diagnostic accuracy and efficiency.

JLK Inc. provides AI-based medical imaging systems across multiple specialties, including neuro, chest, and breast imaging. Their products utilize deep learning models to analyze medical images, aiding in the detection and classification of various conditions such as cerebral aneurysms, lung nodules, and breast tumors. These systems are designed to integrate with existing medical imaging workflows, offering features like lesion detection, quantification, and report generation. Deployment options include local hardware, cloud-based, and hybrid solutions, with processing times ranging from 3 to 60 seconds, depending on the application. Regulatory certifications vary by product, with some holding CE Class I MDD certification and others pending FDA approval. Pricing models typically involve pay-per-use or subscription plans based on the number of users or installations.

Pay-per-use, Subscription; based on number of users, number of installations

South Korea
United States
Germany
Japan
China
India
Brazil
France
United Kingdom
Australia

Segmentation of suspected cerebral aneurysm

Integration with PACS/reading environment

AI marketplace/distribution platform integration

DICOM-compatible imaging input; web browser for web-based deployment; dedicated hardware option for local deployment

BAA available
consent management
anonymization
data minimization


Summary: Mia is an AI-powered breast cancer screening solution developed by Kheiron Medical Technologies, designed to assist radiologists in detecting breast cancer earlier and more accurately.

Mia, or Mammography Intelligent Assessment, is an AI-driven platform that analyzes mammography images to support radiologists in making critical decisions about patient recall for further testing. It can function as an independent second reader, a concurrent reader, or in double reader triage, enhancing diagnostic accuracy and workflow efficiency. Mia has received CE marking in Europe, TGA approval in Australia, and Medsafe registration in New Zealand. It is also available in the UAE and Qatar pending local registration. Additionally, Mia IQ, an AI-enabled image quality assurance tool, is part of the Mia suite, aiding in the improvement of image quality and training for radiographers and radiologists. In 2024, Kheiron Medical Technologies was acquired by DeepHealth, a global leader in AI-powered health informatics, further expanding the reach and capabilities of Mia in breast cancer detection.

radiologists
screening providers
healthcare professionals

United Kingdom
United States
Europe
Australia
New Zealand
UAE
Qatar

Independent second read
Recall suggestion
Suspicious region marking
Image indications

tablet devices (hospital-owned iPads/Android tablets)

FHIR Structured Data Capture (SDC) Implementation Guide v3.0.0

Web browser on tablet (iPad/Android); FHIR-capable HIS/RIS/EHR endpoints; Q&A as separate API service

CE Certification
FDA 510(k)
TGA clearance
MedSafe WAND Notification

privacy statement shown in on-boarding
GDPR-aligned data handling (prototype)

EU-only, US/EU regions, BYO cloud region


Summary: Ligence Heart is an AI-powered web-based platform that automates the analysis and reporting of 2D transthoracic echocardiography, enhancing diagnostic efficiency and accuracy.

Ligence Heart is a web-based, fully integrated echocardiography analysis suite that automates the segmentation, measurement, and reporting of 2D transthoracic echocardiography (TTE) images. It supports integration with PACS and EHR systems, providing guideline-based reports aligned with standards such as EACVI, BSE, and ASE. The platform is CE-certified in the European Union and is pending FDA clearance in the United States. ([nsmedicaldevices.com](https://www.nsmedicaldevices.com/company-news/blackford-partners-with-ligence-medical-ai-solutions-for-echocardiography-ai/?utm_source=openai))

cardiologists
echocardiography sonographers
cardiac imaging physicians
radiologists
clinical administrators
IT/healthcare informatics staff

Cardiology
Echocardiography
Heart Failure
Valvular Heart Disease
Pulmonary Hypertension
Cardiac Imaging

European Union
United States (pending FDA clearance)

Contact vendor for pricing, demos, and trial information

Risk stratification and predictive analytics

Integration with electronic health records (EHR)

Advanced analytics and reporting
Telemedicine integration
Patient engagement tools
Clinical research support
Mobile health applications
Data export and interoperability
Customizable alert thresholds
Multi-language support
User training and support services
System performance optimization

Epic
Cerner
PACS
Billing systems
Laboratory information systems
Patient portals
Medical devices
Wearable health monitors
Telehealth platforms
Clinical decision support systems

Major OS/DB/hardware needs, or empty if SaaS-only

Encryption
RBAC
SSO/SAML
Audit logs
2FA
DLP

BAA available
Consent management
Anonymization
Data minimization


Summary: Prostate Intelligence™ (Pi™) is an AI-driven software developed by Lucida Medical to enhance the accuracy and efficiency of prostate cancer diagnosis through MRI analysis.

Pi™ utilizes advanced image processing, deep learning, and machine learning techniques to automatically segment the prostate, identify regions of interest, and calculate risk scores from MRI scans. It integrates seamlessly into radiologists' workflows, providing 3D visualizations and structured reports to support biopsy planning and treatment decisions. CE-marked as a Class IIb medical device, Pi™ has demonstrated 95% sensitivity and 67% specificity in detecting clinically significant prostate cancer, aiming to reduce unnecessary biopsies and improve diagnostic accuracy. The software is currently available in the UK and EU, with plans for broader distribution pending regulatory approvals in other regions.

Radiologists
Urologists
Oncologists
Medical Imaging Professionals

AI-supported prostate segmentation and volume

3D visualization of prostate, seminal vesicles, and lesions

Automated analysis post-image acquisition

On-demand analysis triggered by user actions

Locally on dedicated hardware deployment

PACS
RIS
Sectra Amplifier Marketplace
TeraRecon Eureka Clinical AI Platform
Blackford
OpenRad
Medical Horizons
HCK Healthcare Konnect
Aplicaciones Tecnológicas Fisica

Data encryption
Role-based access control (RBAC)
Audit logs
Single sign-on (SSO)
Two-factor authentication (2FA)


Summary: mdknee is an AI-powered tool developed by mediaire for the automated analysis of knee MRIs, focusing on the classification of cartilage injuries based on ICRS criteria.

mdknee automates the detection and classification of knee cartilage damage using the International Cartilage Regeneration & Joint Preservation Society (ICRS) grading system. It integrates seamlessly with PACS, generating visual and quantitative reports in under five minutes, and maps affected areas to specific anatomical regions such as the femur, tibia, and patella.

Radiologists
Orthopedic Surgeons
Medical Imaging Professionals

Musculoskeletal Imaging
Orthopedics
Radiology

Knee MRI analysis
3D visualization
Automated measurements
Segmentation tools
Reporting capabilities
Integration with PACS systems
Multi-language support
Cloud storage options
User-friendly interface
Customizable settings

Advanced analytics
AI-powered diagnostics
Telemedicine integration
Patient portal
Mobile app
Data backup solutions
Compliance reporting
Clinical decision support
Workflow optimization
Training resources

PACS systems
Electronic Health Records (EHR)
Hospital Information Systems (HIS)
Laboratory Information Systems (LIS)
Medical Imaging Devices
Cloud storage providers
Third-party analytics tools
Telemedicine platforms
Patient management systems
Billing software

DICOM
HL7
FHIR
ICD-10
SNOMED CT
LOINC
CPT
ICD-11
X12 EDI
HL7 CDA

Windows Server 2016 or later, 8 GB RAM, 500 GB HDD, 1 Gbps network connection

HIPAA
GDPR
SOC 2
ISO 27001
HITECH
FDA 510(k)
CE/MDR
ONC
ISO 13485
ISO 9001

FDA 510(k)
CE/MDR
ONC
ISO 13485
ISO 9001
SOC 2 Type II
ISO 27001
HIPAA
GDPR
HITECH

Encryption
RBAC
SSO/SAML
Audit logs
2FA
DLP
Firewall
Intrusion detection
Data masking
Backup and recovery

BAA available
Consent management
Anonymization
Data minimization
Data residency controls
Access controls
Data retention policies
User data rights management
Data breach notification
Third-party audits


Summary: MediAI-BA is an AI-driven solution by Crescom that automates bone age assessment, skeletal maturity indicators, and adult height prediction using a hybrid Greulich-Pyle and Tanner-Whitehouse algorithm.

MediAI-BA is a web-based AI solution developed by Crescom for the automated analysis of bone age, skeletal maturity indicators, and adult height prediction. Utilizing a patented hybrid algorithm combining Greulich-Pyle and Tanner-Whitehouse methods, it provides rapid analysis of pediatric hand and wrist X-ray images, delivering results within 3 to 10 seconds. The solution integrates seamlessly with hospital systems, including PACS, and offers structured reports in HTML and PDF formats. It has been clinically validated, demonstrating a mean absolute difference of approximately 0.39 years compared to expert assessments. Since its market introduction in March 2020, MediAI-BA has been adopted by over 300 clinical institutions across multiple countries, including South Korea and Japan. The product is CE-certified and approved by the Korean Ministry of Food and Drug Safety (MFDS).

radiologists
pediatricians
orthodontists
endocrinologists
clinicians
hospital administrators
parents/patients (via companion app)

Pediatrics Orthodontics Endocrinology Musculoskeletal

South Korea
Japan
Malaysia
Singapore
United States
European Union

Contact vendor for tiered pricing and trial information.

Bone age assessment using hybrid GP and TW3 methods

Bone age determination for key regions of interest (ROIs)

Predicted adult height calculations (Middle-Parental Height, AHP, BP)