BoneView is an AI Companion for lesion detection on Bone X-Rays. BoneView can detect fractures, effusions, dislocations and bone lesions, and gives 3 different pre-diagnosis labels on the images:
- POSITIVE when the confidence for the presence of a lesion is above 90% (plain bounding box around the region of interest)
- DOUBT when the confidence for the presence of a lesion is between 50% and 90% (dotted bounding box around the region of interest)
- NEGATIVE otherwise

BoneView provides a Summary Table for quality check and overview of AI outputs at a glance, and can perform worklist prioritization according to the different pre-diagnoses.
Product specifications Information source: Vendor
Last updated: Aug. 26, 2021
General
Product name BoneView
Company GLEAMER
Subspeciality MSK
Modality X-ray
Disease targeted bone fractures, effusions, dislocations and bone lesions
Key-features detection of fractures, effusions, dislocations and bone lesions, worklist prioritization
Suggested use Before: adapting worklist order, flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand)
After: diagnosis verification
Data characteristics
Population Adult and pediatric patients with suspicion of fracture
Input bone trauma X-ray
Input format DICOM
Output image annotation, pre-diagnosis
Output format DICOM
Technology
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis Automatically, right after the image acquisition
Processing time 1 - 10 minutes
Certification
CE
Certified, Class IIa , MDD
FDA
No or not yet
Market presence
On market since 03-2020
Distribution channels Incepto, Softway, Fuji Reili, Ferrum, Wellbeing Software, Sectra Amplifier Store
Countries present (clinical, non-research use) 10 (France, Switzerland, Netherlands, Belgium, UK, Germany, Italy, Latvia, New Zealand, UAE)
Paying clinical customers (institutes) 70
Research/test users (institutes) 17
Pricing
Pricing model Subscription
Based on Number of users, Number of installations, Number of analyses
Evidence
Peer reviewed papers on performance

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

Non-peer reviewed papers on performance
Other relevant papers