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Key Features

  • Detection of fractures
  • Dislocations and bone lesions
  • Effusions
  • Worklist prioritization

General Information

Product name

BoneView

Company

Subspeciality

MSK

Modality

X-ray

Disease targeted

Bone fractures, effusions, dislocations and bone lesions

Main task

Not specified

Technical Specifications

Population

Adult and pediatric patients with suspicion of fracture

Patient population age

Not specified

Input

Bone trauma X-ray

Input format

DICOM

Output

Image annotation, pre-diagnosis

Output format

DICOM, DICOM SR, GSPS

Integration

Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform

Deployment

Cloud-based, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

1 - 10 minutes

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIa

Not verified by Health AI Register
FDA Certification

Pathway:

510(k) cleared

Class:

Class II

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

03-2020

AI Platforms

Agfa Healthcare, Aidoc, Bayer Pharmaceuticals, Blackford Analysis, CARPL.AI, Deepc, Ferrum Health, Fujifilm, Incepto, Nuance, Sectra, Siemens Healthineers, TeraRecon

Resellers

RMS Medical Devices

Countries present

>40

Paying clinical customers

>650

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of analyses, Number of installations, Number of users

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

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Added value of artificial intelligence for the detection of pelvic and hip fractures

Peer-Reviewed

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Artificial intelligence (AI) for paediatric fracture detection: a multireader multicase (MRMC) study protocol

Peer-Reviewed

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Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study

Peer-Reviewed

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Effectiveness of an Artificial Intelligence Software for Limb Radiographic Fracture Recognition in an Emergency Department

Peer-Reviewed

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AI-Assisted X-ray Fracture Detection in Residency Training: Evaluation in Pediatric and Adult Trauma Patients

Peer-Reviewed

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Radiographic Detection of Post-Traumatic Bone Fractures: Contribution of Artificial Intelligence Software to the Analysis of Senior and Junior Radiologists

Peer-Reviewed

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AI-based X-ray fracture analysis of the distal radius: accuracy between representative classification, detection and segmentation deep learning models for clinical practice

Peer-Reviewed

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Artificial Intelligence for Detecting Acute Fractures in Patients Admitted to an Emergency Department: Real-Life Performance of Three Commercial Algorithms

Peer-Reviewed

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Artificial intelligence vs. radiologist: accuracy of wrist fracture detection on radiographs

Peer-Reviewed

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A Prospective Approach to Integration of AI Fracture Detection Software in Radiographs into Clinical Workflow

Peer-Reviewed

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Assessment of an artificial intelligence aid for the detection of appendicular skeletal fractures in children and young adults by senior and junior radiologists

Peer-Reviewed

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Added value of an artificial intelligence solution for fracture detection in the radiologist's daily trauma emergencies workflow

Peer-Reviewed

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Assessment of performances of a deep learning algorithm for the detection of limbs and pelvic fractures, dislocations, focal bone lesions, and elbow effusions on trauma X-rays

Peer-Reviewed

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Automated detection of acute appendicular skeletal fractures in pediatric patients using deep learning

Peer-Reviewed

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Improving Radiographic Fracture Recognition Performance and Efficiency Using Artificial Intelligence

Peer-Reviewed

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Assessment of an AI Aid in Detection of Adult Appendicular Skeletal Fractures by Emergency Physicians and Radiologists: A Multicenter Cross-sectional Diagnostic Study

Other Articles

Other

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Implementing Artificial Intelligence for Emergency Radiology Impacts Physicians' Knowledge and Perception - A Prospective Pre- and Post-Analysis

Other

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Abstract ECR 2024: Implementation of an AI Application for Fracture Detection: Major benefits for Patients and Healthcare Workers

Source: vendor | First published: Apr 15, 2024 | Last updated: Jul 10, 2025