VisiRad XR

JSON twin: https://www.healthaidb.com/software/visirad-xr.json

Company Name

Imidex

Product URL

https://imidex.com/visirad/

Company URL

https://imidex.com/

Categories

• diagnostic Support
• clinical Care
• administrative Operations
• Diagnostic
• Clinical
• Administrative

Summary

VisiRad XR is an AI-powered software developed by Imidex to assist radiologists in detecting lung nodules and masses in chest X-rays, aiming to improve early lung cancer detection and patient outcomes.

Description

VisiRad XR utilizes advanced machine learning techniques to analyze chest X-rays, highlighting potential lung nodules and masses. It integrates seamlessly into existing radiology workflows, providing a 'second-read' capability to enhance detection rates without requiring additional testing orders. The software has demonstrated an 83% sensitivity in detecting lung nodules as small as 6mm, potentially identifying up to 750 additional cases annually in a hospital performing 50,000 chest X-rays. Imidex received FDA 510(k) clearance for VisiRad XR in August 2023, marking a significant advancement in AI-assisted medical imaging for lung cancer detection.

Api Available

unknown

Certifications

• FDA 510(k)
• CE Mark
• ISO 13485
• ISO 14971
• IEC 62304
• IEC 62366
• IEC 60601-1
• IEC 60601-1-2
• IEC 60601-1-6
• IEC 62341

Company Founding

2019

Company Offices

• United States

Compliance

• HIPAA
• FDA 510(k)
• GDPR
• ISO 13485
• ISO 14971
• IEC 62304
• IEC 62366
• IEC 60601-1
• IEC 60601-1-2
• IEC 60601-1-6

Customers

• Hospitals
• Radiology practices
• Nodule clinics
• Health systems

Data Residency

US and EU regions

Data Standards

• DICOM
• HL7
• FHIR
• ICD-10
• SNOMED CT
• LOINC
• CPT
• ICD-9
• NDC
• HCPCS

Deployment Model

• SaaS

Features

• AI-powered detection of lung nodules and masses in chest X-rays
• Integrates into existing radiology workflows
• Highlights AI-detected lesions within native viewing environments
• Requires no additional testing orders
• Improves detection sensitivity to 83% in clinical studies
• Enhances radiologist performance and reduces burnout
• Developed using curated global training data
• FDA 510(k) cleared for clinical use
• Supports outpatient and emergency department settings
• Provides a 'second-read' for lung nodules and masses
• Potential to identify up to 750 additional lung nodules or masses annually per hospital
• Utilizes machine learning techniques for analysis
• Offers a cost-effective alternative to CT scans
• Designed to detect nodules as small as 6mm
• Supports early-stage lung cancer detection
• Improves early detection rates of lung cancer
• Enhances patient outcomes through early intervention
• Integrates with existing imaging systems
• Supports high-volume chest X-ray screenings
• Provides real-time analysis and feedback to radiologists

Id

SW0326

Integration Partners

• Google Cloud
• Spesana
• Orbit Genomics

Integrations

• Spesana's medical data platform
• Google Cloud's VertexAI
• Existing radiology imaging systems
• DICOM image formats
• Annotation tools for data labeling
• Clinical study platforms
• Medical data management systems
• Healthcare provider IT systems
• Radiology information systems (RIS)
• Picture archiving and communication systems (PACS)

Languages Supported

• English

Last Updated

2025-10-11

License

commercial

Market Segment

• enterprise
• smb

Optional Modules

• Clinical validation studies
• Standalone performance studies
• Integration with Spesana's medical data platform
• Integration with Google Cloud's VertexAI
• Custom workflows for data labeling and annotation
• DICOM image support
• Annotation tracking features
• Quality assurance processes
• Consensus stages in data labeling
• Blind reads for clinical studies

Os Platforms

• Web

Pricing Details

contact vendor

Pricing Model

subscription

Privacy Features

• Business Associate Agreement (BAA)
• Data anonymization
• Data minimization
• Patient consent management
• Data access controls
• Data retention policies
• Data masking
• Secure data storage
• Compliance with privacy regulations
• User data protection measures

Product Code

SW0326

Product Name

VisiRad XR

Ratings

• FDA 510(k) clearance achieved in August 2023.

Regions Available

• United States

Related Urls

• https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices

Release Year

2023

Security Features

• Data encryption
• Role-based access control (RBAC)
• Single sign-on (SSO)
• Audit logs
• Two-factor authentication (2FA)
• Data loss prevention (DLP)
• Secure data transmission
• Regular security updates
• Compliance with security standards
• User authentication mechanisms

Specialties

• Pulmonology
• Oncology
• Radiology

Support Channels

• email
• phone
• chat
• ticketing
• community
• 24x7

System Requirements

Web browser with internet access

Target Users

• radiologists
• clinicians
• healthcare providers

Training Options

• documentation
• webinars
• live_online
• onsite
• certification

Type

product

User Reviews

• "VisiRad XR has significantly improved our detection rates for lung nodules.", "The integration into our existing workflow was seamless.", "Radiologists find the AI assistance invaluable in routine screenings."

Version

1.0

Alternatives

See related products

Canonical JSON

{
  "product_name": "VisiRad XR",
  "company_name": "Imidex",
  "product_url": "https://imidex.com/visirad/",
  "company_url": "https://imidex.com/",
  "related_urls": [
    "https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"
  ],
  "product_code": "SW0326",
  "summary": "VisiRad XR is an AI-powered software developed by Imidex to assist radiologists in detecting lung nodules and masses in chest X-rays, aiming to improve early lung cancer detection and patient outcomes.",
  "description": "VisiRad XR utilizes advanced machine learning techniques to analyze chest X-rays, highlighting potential lung nodules and masses. It integrates seamlessly into existing radiology workflows, providing a 'second-read' capability to enhance detection rates without requiring additional testing orders. The software has demonstrated an 83% sensitivity in detecting lung nodules as small as 6mm, potentially identifying up to 750 additional cases annually in a hospital performing 50,000 chest X-rays. Imidex received FDA 510(k) clearance for VisiRad XR in August 2023, marking a significant advancement in AI-assisted medical imaging for lung cancer detection.",
  "categories": [
    "diagnostic Support",
    "clinical Care",
    "administrative Operations",
    "Diagnostic",
    "Clinical",
    "Administrative"
  ],
  "market_segment": [
    "enterprise",
    "smb"
  ],
  "target_users": [
    "radiologists",
    "clinicians",
    "healthcare providers"
  ],
  "specialties": [
    "Pulmonology",
    "Oncology",
    "Radiology"
  ],
  "regions_available": [
    "United States"
  ],
  "languages_supported": [
    "English"
  ],
  "pricing_model": "subscription",
  "pricing_details": "contact vendor",
  "license": "commercial",
  "company_offices": [
    "United States"
  ],
  "company_founding": "2019",
  "deployment_model": [
    "SaaS"
  ],
  "os_platforms": [
    "Web"
  ],
  "features": [
    "AI-powered detection of lung nodules and masses in chest X-rays",
    "Integrates into existing radiology workflows",
    "Highlights AI-detected lesions within native viewing environments",
    "Requires no additional testing orders",
    "Improves detection sensitivity to 83% in clinical studies",
    "Enhances radiologist performance and reduces burnout",
    "Developed using curated global training data",
    "FDA 510(k) cleared for clinical use",
    "Supports outpatient and emergency department settings",
    "Provides a 'second-read' for lung nodules and masses",
    "Potential to identify up to 750 additional lung nodules or masses annually per hospital",
    "Utilizes machine learning techniques for analysis",
    "Offers a cost-effective alternative to CT scans",
    "Designed to detect nodules as small as 6mm",
    "Supports early-stage lung cancer detection",
    "Improves early detection rates of lung cancer",
    "Enhances patient outcomes through early intervention",
    "Integrates with existing imaging systems",
    "Supports high-volume chest X-ray screenings",
    "Provides real-time analysis and feedback to radiologists"
  ],
  "optional_modules": [
    "Clinical validation studies",
    "Standalone performance studies",
    "Integration with Spesana's medical data platform",
    "Integration with Google Cloud's VertexAI",
    "Custom workflows for data labeling and annotation",
    "DICOM image support",
    "Annotation tracking features",
    "Quality assurance processes",
    "Consensus stages in data labeling",
    "Blind reads for clinical studies"
  ],
  "integrations": [
    "Spesana's medical data platform",
    "Google Cloud's VertexAI",
    "Existing radiology imaging systems",
    "DICOM image formats",
    "Annotation tools for data labeling",
    "Clinical study platforms",
    "Medical data management systems",
    "Healthcare provider IT systems",
    "Radiology information systems (RIS)",
    "Picture archiving and communication systems (PACS)"
  ],
  "data_standards": [
    "DICOM",
    "HL7",
    "FHIR",
    "ICD-10",
    "SNOMED CT",
    "LOINC",
    "CPT",
    "ICD-9",
    "NDC",
    "HCPCS"
  ],
  "api_available": "unknown",
  "system_requirements": "Web browser with internet access",
  "compliance": [
    "HIPAA",
    "FDA 510(k)",
    "GDPR",
    "ISO 13485",
    "ISO 14971",
    "IEC 62304",
    "IEC 62366",
    "IEC 60601-1",
    "IEC 60601-1-2",
    "IEC 60601-1-6"
  ],
  "certifications": [
    "FDA 510(k)",
    "CE Mark",
    "ISO 13485",
    "ISO 14971",
    "IEC 62304",
    "IEC 62366",
    "IEC 60601-1",
    "IEC 60601-1-2",
    "IEC 60601-1-6",
    "IEC 62341"
  ],
  "security_features": [
    "Data encryption",
    "Role-based access control (RBAC)",
    "Single sign-on (SSO)",
    "Audit logs",
    "Two-factor authentication (2FA)",
    "Data loss prevention (DLP)",
    "Secure data transmission",
    "Regular security updates",
    "Compliance with security standards",
    "User authentication mechanisms"
  ],
  "privacy_features": [
    "Business Associate Agreement (BAA)",
    "Data anonymization",
    "Data minimization",
    "Patient consent management",
    "Data access controls",
    "Data retention policies",
    "Data masking",
    "Secure data storage",
    "Compliance with privacy regulations",
    "User data protection measures"
  ],
  "data_residency": "US and EU regions",
  "customers": [
    "Hospitals",
    "Radiology practices",
    "Nodule clinics",
    "Health systems"
  ],
  "user_reviews": [
    "\"VisiRad XR has significantly improved our detection rates for lung nodules.\", \"The integration into our existing workflow was seamless.\", \"Radiologists find the AI assistance invaluable in routine screenings.\""
  ],
  "ratings": [
    "FDA 510(k) clearance achieved in August 2023."
  ],
  "support_channels": [
    "email",
    "phone",
    "chat",
    "ticketing",
    "community",
    "24x7"
  ],
  "training_options": [
    "documentation",
    "webinars",
    "live_online",
    "onsite",
    "certification"
  ],
  "release_year": "2023",
  "integration_partners": [
    "Google Cloud",
    "Spesana",
    "Orbit Genomics"
  ],
  "id": "SW0326",
  "slug": "visirad-xr",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/visirad-xr.json"
  }
}