OsteoDetect

JSON twin: https://www.healthaidb.com/software/osteodetect.json

Company Name

Imagen Technologies

Product URL

https://www.imagen-tech.com/osteodetect

Company URL

https://www.imagen-tech.com

Categories

• diagnostic Support
• clinical Decision Support
• radiology
• ai Clinical Documentation Integrity
• Diagnostic
• Artificial Intelligence

Summary

OsteoDetect is an AI-driven software developed by Imagen Technologies to assist clinicians in detecting distal radius fractures in adult wrist X-rays, enhancing diagnostic accuracy and speed.

Description

OsteoDetect utilizes machine learning algorithms to analyze posterior-anterior and lateral wrist radiographs, identifying and highlighting potential distal radius fractures. It serves as an adjunct tool, supporting clinicians in various settings, including primary care, emergency medicine, urgent care, and orthopedics, without replacing their clinical judgment. The software was granted FDA marketing authorization in May 2018 through the De Novo premarket review pathway, demonstrating improved diagnostic performance in detecting wrist fractures compared to unaided clinical practice.

Api Available

yes

Certifications

• FDA 510(k)
• CE Marking
• ISO 13485
• ISO 14971
• IEC 62304
• IEC 62366
• IEC 60601-1
• IEC 60601-1-2
• IEC 60601-1-6
• IEC 60601-1-8

Company Founding

2016

Company Offices

• United States

Compliance

• HIPAA
• GDPR
• HITECH
• SOC 2
• ISO 27001
• FDA 21 CFR Part 820
• FDA 21 CFR Part 11
• ISO 13485
• ISO 14971
• IEC 62304

Customers

Data Residency

US/EU regions

Data Standards

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

Deployment Model

• SaaS
• on_prem
• hybrid

Features

• AI-driven detection of distal radius fractures in adult wrist X-rays
• Analysis of both posterior-anterior and lateral radiographs
• Bounding boxes highlighting potential fractures
• Supports CR and DR DICOM images
• Preprocessing and postprocessing of images
• Deep learning model for fracture detection
• Confidence scoring for detected fractures
• Integration with PACS for annotated DICOM images
• Standalone software validation
• Clinical reader study validation
• High diagnostic accuracy (AUC 0.965)
• High sensitivity (92.1%) and specificity (90.2%)
• Improved diagnostic accuracy with AI assistance
• Localization accuracy testing
• Generalizability across patient subgroups and device types
• FDA-cleared as a Computer-Aided Detection and Diagnosis (CADe/x) software
• Validated through large-scale clinical trials
• Developed in collaboration with leading research hospitals
• Supports early detection and intervention to reduce medical expenses

Id

SW0590

Integration Partners

Integrations

• PACS
• EHR systems
• Cloud storage solutions
• Telemedicine platforms
• Mobile devices
• Clinical decision support systems
• Reporting and analytics tools
• Patient management systems
• Remote monitoring devices
• Patient education platforms

Languages Supported

• English

Last Updated

2025-10-11

License

commercial

Market Segment

• enterprise
• smb

Optional Modules

• Clinical decision support tools
• Advanced image processing features
• Integration with electronic health records (EHR) systems
• Patient management modules
• Reporting and analytics tools
• Mobile application for clinicians
• Cloud-based storage solutions
• Telemedicine integration
• Patient education resources
• Remote monitoring capabilities

Os Platforms

• Web
• iOS
• Android
• Windows
• macOS
• Linux

Pricing Details

contact vendor

Pricing Model

subscription

Privacy Features

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

Product Code

SW0590

Product Name

OsteoDetect

Ratings

Regions Available

• United States

Related Urls

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

Release Year

Security Features

• Encryption
• RBAC
• SSO/SAML
• Audit logs
• 2FA
• DLP
• Secure APIs
• Data anonymization
• Regular security updates
• Incident response protocols

Specialties

• Orthopedics
• Emergency Medicine
• Urgent Care
• Primary Care

Support Channels

System Requirements

• Windows Server 2016 or later
• Linux (Ubuntu 18.04 or later)
• macOS Mojave or later
• iOS 12 or later
• Android 9.0 or later
• 2 GB RAM minimum
• 500 MB free disk space
• Internet connection for cloud features

Target Users

• clinicians
• radiologists
• orthopedic surgeons
• emergency medicine providers
• urgent care providers

Training Options

Type

product

User Reviews

Version

1.0

Alternatives

See related products

Canonical JSON

{
  "product_name": "OsteoDetect",
  "company_name": "Imagen Technologies",
  "product_url": "https://www.imagen-tech.com/osteodetect",
  "company_url": "https://www.imagen-tech.com",
  "related_urls": [
    "https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-enabled-medical-devices"
  ],
  "product_code": "SW0590",
  "summary": "OsteoDetect is an AI-driven software developed by Imagen Technologies to assist clinicians in detecting distal radius fractures in adult wrist X-rays, enhancing diagnostic accuracy and speed.",
  "description": "OsteoDetect utilizes machine learning algorithms to analyze posterior-anterior and lateral wrist radiographs, identifying and highlighting potential distal radius fractures. It serves as an adjunct tool, supporting clinicians in various settings, including primary care, emergency medicine, urgent care, and orthopedics, without replacing their clinical judgment. The software was granted FDA marketing authorization in May 2018 through the De Novo premarket review pathway, demonstrating improved diagnostic performance in detecting wrist fractures compared to unaided clinical practice.",
  "categories": [
    "diagnostic Support",
    "clinical Decision Support",
    "radiology",
    "ai Clinical Documentation Integrity",
    "clinical Decision Support",
    "Diagnostic",
    "Clinical Decision Support",
    "Radiology",
    "Artificial Intelligence"
  ],
  "market_segment": [
    "enterprise",
    "smb"
  ],
  "target_users": [
    "clinicians",
    "radiologists",
    "orthopedic surgeons",
    "emergency medicine providers",
    "urgent care providers"
  ],
  "specialties": [
    "Orthopedics",
    "Emergency Medicine",
    "Urgent Care",
    "Primary Care"
  ],
  "regions_available": [
    "United States"
  ],
  "languages_supported": [
    "English"
  ],
  "pricing_model": "subscription",
  "pricing_details": "contact vendor",
  "license": "commercial",
  "company_offices": [
    "United States"
  ],
  "company_founding": "2016",
  "deployment_model": [
    "SaaS",
    "on_prem",
    "hybrid"
  ],
  "os_platforms": [
    "Web",
    "iOS",
    "Android",
    "Windows",
    "macOS",
    "Linux"
  ],
  "features": [
    "AI-driven detection of distal radius fractures in adult wrist X-rays",
    "Analysis of both posterior-anterior and lateral radiographs",
    "Bounding boxes highlighting potential fractures",
    "Supports CR and DR DICOM images",
    "Preprocessing and postprocessing of images",
    "Deep learning model for fracture detection",
    "Confidence scoring for detected fractures",
    "Integration with PACS for annotated DICOM images",
    "Standalone software validation",
    "Clinical reader study validation",
    "High diagnostic accuracy (AUC 0.965)",
    "High sensitivity (92.1%) and specificity (90.2%)",
    "Improved diagnostic accuracy with AI assistance",
    "Localization accuracy testing",
    "Generalizability across patient subgroups and device types",
    "FDA-cleared as a Computer-Aided Detection and Diagnosis (CADe/x) software",
    "Validated through large-scale clinical trials",
    "Developed in collaboration with leading research hospitals",
    "Supports early detection and intervention to reduce medical expenses"
  ],
  "optional_modules": [
    "Clinical decision support tools",
    "Advanced image processing features",
    "Integration with electronic health records (EHR) systems",
    "Patient management modules",
    "Reporting and analytics tools",
    "Mobile application for clinicians",
    "Cloud-based storage solutions",
    "Telemedicine integration",
    "Patient education resources",
    "Remote monitoring capabilities"
  ],
  "integrations": [
    "PACS",
    "EHR systems",
    "Cloud storage solutions",
    "Telemedicine platforms",
    "Mobile devices",
    "Clinical decision support systems",
    "Reporting and analytics tools",
    "Patient management systems",
    "Remote monitoring devices",
    "Patient education platforms"
  ],
  "data_standards": [
    "DICOM",
    "HL7",
    "FHIR",
    "ICD-10",
    "SNOMED CT",
    "LOINC",
    "CPT",
    "HL7 CDA",
    "HL7 CCD",
    "HL7 CCDS"
  ],
  "api_available": "yes",
  "system_requirements": [
    "Windows Server 2016 or later",
    "Linux (Ubuntu 18.04 or later)",
    "macOS Mojave or later",
    "iOS 12 or later",
    "Android 9.0 or later",
    "2 GB RAM minimum",
    "500 MB free disk space",
    "Internet connection for cloud features"
  ],
  "compliance": [
    "HIPAA",
    "GDPR",
    "HITECH",
    "SOC 2",
    "ISO 27001",
    "FDA 21 CFR Part 820",
    "FDA 21 CFR Part 11",
    "ISO 13485",
    "ISO 14971",
    "IEC 62304"
  ],
  "certifications": [
    "FDA 510(k)",
    "CE Marking",
    "ISO 13485",
    "ISO 14971",
    "IEC 62304",
    "IEC 62366",
    "IEC 60601-1",
    "IEC 60601-1-2",
    "IEC 60601-1-6",
    "IEC 60601-1-8"
  ],
  "security_features": [
    "Encryption",
    "RBAC",
    "SSO/SAML",
    "Audit logs",
    "2FA",
    "DLP",
    "Secure APIs",
    "Data anonymization",
    "Regular security updates",
    "Incident response protocols"
  ],
  "privacy_features": [
    "BAA available",
    "Consent management",
    "Data anonymization",
    "Data minimization",
    "Data residency options",
    "Access controls",
    "Data retention policies",
    "User data rights management",
    "Data breach notification procedures",
    "Third-party audits"
  ],
  "data_residency": "US/EU regions",
  "customers": [],
  "user_reviews": [],
  "ratings": [],
  "support_channels": [],
  "training_options": [],
  "release_year": "",
  "integration_partners": [],
  "id": "SW0590",
  "slug": "osteodetect",
  "type": "product",
  "version": "1.0",
  "last_updated": "2025-10-11",
  "links_json": {
    "self": "https://www.healthaidb.com/software/osteodetect.json"
  }
}