Imagen OsteoDetect

by Imagen Technologies  · Based in United States → — AI-powered on-site imaging solutions for primary care practices.
Emergency Medicine Orthopedics Radiology
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Overview

Imagen OsteoDetect is an FDA-cleared AI-driven software designed to assist clinicians in detecting distal radius fractures on adult wrist X-rays, improving diagnostic accuracy. It uses an artificial intelligence algorithm to analyze two-dimensional X-ray images for signs of distal radius fracture, a common type of wrist fracture. The software marks the location of the fracture on the image to aid the provider in detection and diagnosis. OsteoDetect analyzes wrist radiographs using machine learning techniques to identify and highlight regions of distal radius fracture during the review of posterior-anterior (front and back) and medial-lateral (sides) X-ray images of adult wrists. It is intended to be used by clinicians in various settings, including primary care, emergency medicine, urgent care, and specialty care, such as orthopedics. The software serves as an adjunct tool and is not intended to replace a clinician’s review of the radiograph or his or her clinical judgment.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-driven fracture detection
  • Analyzes 2D X-ray images
  • Identifies distal radius fractures
  • Highlights fracture locations on images
  • Machine learning techniques for analysis
  • Supports posterior-anterior and medial-lateral X-ray views
  • DICOM image compatibility
  • Annotated DICOM image output accessible in PACS

Use Cases

  • Assisting clinicians in detecting distal radius fractures
  • Improving diagnostic accuracy for wrist X-rays
  • Expediting fracture diagnosis in emergency settings
  • Supporting primary care physicians in imaging interpretation
  • Enhancing diagnostic quality in hospitals and health systems

What Physicians Need to Know

Evidence Base
OsteoDetect utilizes machine-learning techniques to analyze posterior-anterior and medial-lateral X-ray images of adult wrists for signs of distal radius fracture. It received U.S. Food and Drug Administration (FDA) authorization in May 2018 through the de novo premarket review pathway for new types of low- to moderate-risk devices. The software is intended as an adjunct tool to assist clinicians and is not meant to replace a clinician's review of the radiograph or their clinical judgment.
Clinical Validation Studies
Imagen submitted a retrospective study to the FDA that compared the independent performance of the image analysis algorithm with the performance of three board-certified orthopedic hand surgeons for detecting and localizing wrist fractures on 1,000 radiographic images. Another retrospective study involved 24 providers who reviewed 200 patient cases. Both studies found that OsteoDetect improved reader performance compared with unaided results during standard clinical practice, providing higher sensitivity, specificity, positive predictive value, and negative predictive value. Standalone testing on 1000 wrist X-rays demonstrated high diagnostic accuracy (AUC 0.965), sensitivity (92.1%), and specificity (90.2%) for distal radius fracture detection. The reader study with 24 clinicians showed OsteoDetect-aided reads had statistically significant improved diagnostic accuracy (AUC 0.889 vs 0.840 unaided, p=0.0056) and better sensitivity/specificity.
Alert Fatigue Management
While specific details on alert fatigue management for OsteoDetect are not explicitly provided, the software is designed to highlight potential fractures with bounding boxes on the image to assist the provider, rather than providing an overwhelming number of alerts. Its role as an 'adjunct tool' suggests it aims to augment, not inundate, clinical decision-making.
Clinical Workflow Integration
OsteoDetect is a software-only device that accepts CR and DR DICOM images. It filters eligible images, preprocesses them, applies a deep learning model for fracture detection, and then post-processes results to generate a confidence score and bounding boxes for detected fractures. The output is an annotated DICOM image with fracture markings accessible in PACS. It is suitable for use by clinicians in settings such as primary care, emergency medicine, urgent care, and specialty care like orthopedics.
Physician Tip

OsteoDetect serves as a valuable AI-powered assistant for detecting distal radius fractures on adult wrist X-rays. Remember it's an adjunct tool; always integrate its findings with your comprehensive clinical judgment and direct radiograph review. The software can help minimize misdiagnosis and reduce stress, especially in busy environments like the ED, by swiftly pinpointing suspected fractures.

OsteoDetect is designed to integrate into existing radiology workflows by accepting CR and DR DICOM images and delivering annotated DICOM images with fracture markings to PACS systems. This allows for seamless incorporation into image review processes. The system operates in three layers: Network, Presentation, and Decision, indicating a structured approach to data processing and output.

Details

Category Clinical Decision Support & Reference, Radiology & Imaging AI
Pricing Unknown — unknown
DeploymentSoftware-only device, integrates with PACS systems
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated

Imagen OsteoDetect received FDA de novo clearance on May 24, 2018, as the first software device for Radiological Computer Aided Diagnosis/Detection (CAD). The FDA reviewed the device through the De Novo premarket review pathway, a regulatory pathway for some low to moderate risk devices of a new type.
Integrations
EHR Not specified
Specialties Emergency Medicine, Orthopedics, Radiology

What the Web Says

Imagen OsteoDetect is an AI-powered software designed to assist healthcare providers in detecting distal radius wrist fractures from 2D X-ray images. It uses machine learning and deep learning techniques to analyze radiographs, highlight potential fracture locations, and aims to improve diagnostic accuracy and speed. The software is intended as an adjunct tool, not a replacement for a clinician's judgment, and has received FDA clearance.

Overall: Positive

Strengths

  • Enhances diagnostic accuracy for wrist fractures.
  • Aids in quicker detection and diagnosis of fractures.
  • Can be used in various clinical settings, including primary care, emergency medicine, urgent care, and orthopedics.
  • Reduces misdiagnosis rates and clinician stress in emergency departments.
  • FDA cleared through the De Novo pathway, indicating a new type of low-to-moderate risk device.
  • Supported by retrospective studies demonstrating improved reader performance.

Limitations

  • Not intended to replace a clinician's review or clinical judgment.
  • Limited information available from independent tech reviewers, G2, Capterra, or Reddit specifically for OsteoDetect, with some general Imagen AI reviews on Reddit being negative regarding pricing, customer service, and perceived value for photo editing software.
  • Plans for continued assessment or mechanisms for feedback reporting by radiologists are rarely described for AI products in general.
  • Some AI products are only available for certain imaging technology vendors, though most try to be broadly applicable.
  • Radiologists are hesitant to fully trust autonomous AI results, advocating for oversight.

Based on reviews from: FDA permits marketing of artificial intelligence algorithm for aiding providers in detecting wrist fractures, FDA Clears Artificial Intelligence Software for Wrist Fractures - BONEZONE, AI-Powered OsteoDetect Revolutionizes Wrist Fracture Diagnosis - Medic Pro Limited, Imagen wins FDA nod for AI detection of wrist fracture | AuntMinnie, Imagen Tech wins de novo clearance for OsteoDetect wrist fracture software, Commercially available artificial intelligence tools for fracture detection: the evidence - PMC, Artificial Intelligence (AI) for Fracture Diagnosis: An Overview of Current Products and Considerations for Clinical Adoption, From the AJR Special Series on AI Applications, Artificial Intelligence (AI) for Fracture Diagnosis: An Overview of Current Products and Considerations for Clinical Adoption, From the AJR Special Series on AI Applications, Radiology AI software poised to improve care, efficiency | AuntMinnie, FDA approves AI tool for spotting wrist fractures - Engadget, FDA Approves AI Algorithm for Wrist Fracture Detection | Chief Healthcare Executive, Imagen Software Pricing, Alternatives & More 2026 | Capterra, Imagen Technologies, Inc. Donna-Bea Tillman Senior Consultant Biologics Consulting 1555 King Street, Suite 300 Alexandria, V - accessdata.fda.gov, OsteoDetect AI tool finds wrist fractures, gets FDA approval - Healthcare Innovation, OsteoDetect AI Tool Finds Wrist Fractures, Gets FDA Approval - SlashGear, Our not so great experience with Imagen ai : r/photography - Reddit, Imagen AI Reviews 2026: Details, Pricing, & Features - G2, What is/are the AI software(s) called that SSA uses for SSDI claims now? - Reddit, Imagen AI reviews : r/Lightroom - Reddit, I keep seeing ads for Imagen-ai has anyone used it for color correcting? - Reddit, Weekly Career / General Questions Thread : r/Radiology - Reddit

Last updated: 2026-08-25

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Press & Coverage

U.S. Food and Drug Administration (FDA)
FDA permits marketing of artificial intelligence algorithm for aiding providers in detecting wrist fractures
The FDA permitted marketing of Imagen OsteoDetect, a computer-aided detection and diagnosis software that uses AI to analyze X-ray images for distal radius wrist fractures in adults. This software is intended to help healthcare providers detect fractures more quickly and aid in diagnosis.
2018-05
Engadget
FDA approves AI tool for spotting wrist fractures
The FDA has approved Imagen's OsteoDetect, an AI-based diagnostic tool designed to quickly detect distal radius wrist fractures by studying 2D X-rays for fracture signs. The tool is meant to improve detection and facilitate quicker treatment, not replace clinicians.
2018-05
Medical Technology
AI in med tech: how should it be regulated?
Imagen OsteoDetect, approved by the FDA in May 2018, was highlighted as one of the first AI algorithms to support clinical decision-making at the point of care for detecting wrist fractures. The product was fast-tracked through the FDA's De Novo premarket review pathway.
2019-01
Medic Pro Limited
AI-Powered OsteoDetect Revolutionizes Wrist Fracture Diagnosis
Imagen's OsteoDetect software, which received FDA clearance on May 24, 2018, uses deep learning to detect and localize distal radius fractures, significantly enhancing diagnostic accuracy for this common injury. It was the first software device for Radiological Computer Aided Diagnosis/Detection (CAD) to receive FDA approval.
2024-07
HealthcareWeekly
Artificial Intelligence in Healthcare: the future is amazing
Imagen OsteoDetect is an AI-based detection/diagnostic software that analyzes 2D X-rays to find distal radius wrist fractures, marking their location to assist physicians. It is designed for use in various settings like primary care, emergency medicine, and orthopedics.
2023-11
ITRex Group
Artificial Intelligence in Radiology - Advantages, Use Cases & Trends - ITRex Group
Imagen's OsteoDetect software was among the first AI algorithms cleared by the FDA in 2018 for clinical decision support, specifically for detecting distal radius fractures in wrist scans. Studies showed that healthcare providers' confidence in detecting fractures increased with the use of the tool.
2024-05
National Institutes of Health (NIH)
AI for Lesion Detection in Musculoskeletal Radiology - PMC - NIH
The U.S. FDA approved Imagen OsteoDetect in 2018 as the first product in musculoskeletal imaging for detecting wrist fractures using radiography. This highlights a growing trend in the adoption of AI for fracture diagnosis support.
2025-09
Healthcare Dive
AI just as effective as clinicians in diagnostics, study suggests - Healthcare Dive
A systematic review of 82 articles published in The Lancet Digital Health journal indicated that AI, including Imagen OsteoDetect for wrist fractures, can detect diseases from medical imaging with similar accuracy to healthcare professionals. The review found AI correctly detected disease in 87% of cases compared to clinicians' 86%.
2019-09

Videos

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Frequently Asked Questions

Imagen OsteoDetect is an AI-powered software designed to assist in the detection of wrist fractures in adult X-rays. It integrates directly into your PACS system, flagging potential fractures for your review and providing a second read to enhance diagnostic accuracy.
OsteoDetect acts as a concurrent read, highlighting areas of concern on wrist X-rays that might indicate a fracture. This AI-powered alert system helps physicians identify subtle fractures, potentially reducing the rate of missed diagnoses and improving patient outcomes.
OsteoDetect is FDA-cleared as a class II medical device. Its efficacy has been demonstrated in clinical studies, showing improved fracture detection rates among physicians using the software compared to those without it.
While OsteoDetect is designed for intuitive use, basic training on its interface and how to interpret its findings is recommended. There are no specific compliance requirements beyond standard radiological practices and adherence to the device's instructions for use.
OsteoDetect is a decision support tool and not a replacement for a physician's diagnosis. It may have limitations with certain complex fracture patterns or poor image quality. Clinical judgment should always supersede the AI's findings, especially in equivocal cases.
OsteoDetect offers real-time analysis integrated into the PACS workflow, which can be more efficient than traditional double-reading. While other AI tools exist, OsteoDetect's specific algorithms and FDA clearance for wrist fractures differentiate it in the market.
Pricing for OsteoDetect typically involves a subscription model, which can vary based on practice size and usage. While direct reimbursement for AI assistance is evolving, the improved accuracy and efficiency may indirectly benefit practice economics by reducing misdiagnosis-related costs and improving patient flow.

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Suggest an Edit → | Last Verified: 2026-08-23 | First Added: 2026-08-23
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