OsteoDetect
Overview
OsteoDetect, developed by Imagen Technologies, is an FDA-cleared software device designed to assist clinicians in detecting distal radius fractures in adult wrist radiographs. Utilizing machine learning techniques, it analyzes posterior-anterior (PA) and lateral (LAT) X-ray images to identify and highlight regions suggestive of a fracture by creating a bounding box with a clear label. This AI-powered tool acts as an adjunct, intended to be used concurrently with a clinician’s review of the original, unannotated radiographs, and is not meant to replace clinical judgment or serve as a primary diagnostic read. It has demonstrated in clinical studies to improve clinician performance in detecting wrist fractures, including increased sensitivity and specificity.
Reviewed by Pouyan Golshani, MD — Interventional Radiologist
Key Features
- AI-powered detection of distal radius fractures
- Analyzes posterior-anterior (PA) and lateral (LAT) wrist radiographs
- Highlights fractures with bounding boxes and labels
- Adjunct tool to assist clinicians in diagnosis
- Software-only medical device
- Accepts DICOM image input
- Improved clinician sensitivity and specificity in fracture detection
- Integrates with existing imaging workflows (e.g., PACS systems for image viewing)
Use Cases
- Aiding clinicians in the detection of distal radius wrist fractures
- Use in primary care settings to improve diagnostic accuracy
- Assisting emergency medicine and urgent care providers in fracture identification
- Enhancing orthopedic diagnostic workflows
- Reducing misinterpretation rates of musculoskeletal injuries on X-rays
What Physicians Need to Know
OsteoDetect serves as a valuable assistive tool for detecting distal radius fractures on wrist X-rays, particularly beneficial in high-volume settings like emergency departments or urgent care. Always review the AI-annotated images concurrently with the original, unaltered radiographs and integrate the findings with your clinical judgment. The software is intended to augment, not replace, the clinician's diagnostic role. Its high sensitivity and specificity can help reduce misinterpretation rates, especially for less experienced clinicians, but a thorough review remains paramount.
OsteoDetect integrates directly into existing PACS workflows by presenting annotated and original images within the same patient study. This seamless integration minimizes disruption to the reading room workflow. Ensure your PACS system is configured to properly display DICOM overlays and that images have correct DICOM tags for optimal performance. The system requires a dedicated physical machine with specific hardware requirements for deployment within the institution's DICOM network.
Details
| Category | Radiology & Imaging AI |
| Pricing | Contact vendor for pricing — Contact vendor for pricing |
| Deployment | Cloud-based, Software-only |
| Compliance | |
| BAA Available | Unknown AI-estimated |
| HIPAA Compliant | Unknown AI-estimated |
| FDA Status |
1 AI-estimated OsteoDetect received FDA marketing authorization (De Novo premarket review pathway, DEN180005) on May 24, 2018, as a Class II device (21 CFR 892.2090, Product Code QBS). It is indicated for analyzing wrist radiographs using machine learning techniques to identify and highlight distal radius fractures in adult wrists. |
| Integrations | |
| EHR | Not specified |
| Specialties | Emergency Medicine, Orthopedics, Radiology |
What the Web Says
OsteoDetect, developed by Imagen Technologies, is an AI-powered software designed to assist healthcare providers in detecting distal radius fractures (wrist fractures) in adult X-ray images. It received FDA clearance in May 2018 as the first software device for Radiological Computer Aided Diagnosis/Detection (CAD). The software analyzes 2D X-ray images, identifies potential fractures, and marks their location to aid clinicians in diagnosis, aiming to improve accuracy and efficiency in various settings like emergency rooms, urgent care, and primary care.
Overall: PositiveStrengths
- Improved accuracy in detecting wrist fractures, with studies showing increased sensitivity and specificity.
- Faster diagnosis times, helping clinicians quickly spot and diagnose fractures.
- Reduces misdiagnosis rates, particularly for distal radius fractures, which are commonly misdiagnosed.
- Acts as an adjunct tool, supporting clinicians without replacing their professional judgment.
- Can be used in various clinical settings, including emergency rooms, primary care, and urgent care.
- Potentially reduces physician overload and burnout by streamlining diagnostic workflows.
Limitations
- Only designed to detect distal radius fractures, not other types of fractures or pathologies.
- Requires clinicians to review annotated images concurrently with original images and not use the AI output as the primary interpretation.
- Performance may be reduced on images that do not have correct DICOM tags.
- Limited information available from independent tech reviewers, Reddit, G2, or Capterra specifically for OsteoDetect, with most reviews for Imagen AI focusing on photography editing software.
Based on reviews from: SlashGear, FDA, AuntMinnie, businessabc, PMC, BONEZONE, Medic Pro Limited, Chief Healthcare Executive, Imagen AI, Trustpilot
Last updated: 2026-07-18
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AI Applications for Bone Fracture Detection #sciencefather #aisawards
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