BoneAge

GLEAMER
BoneAge automates the bone age assessment according to the Greulich & Pyle atlas. It aims at overcoming the problem of considerable reader variability of manual ratings.
Information source: Vendor
Last updated: October 29, 2024

General Information

General
Product name BoneAge
Company GLEAMER
Subspeciality MSK
Modality X-ray
Disease targeted Early or late puberty, Congenital Adrenal Hyperplasia (CAH), orthopedic treatment planning, sports medicine, clinical trials
Key-features Bone age assessment
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps)

Technical Specifications

Data characteristics
Population Children from 3 to 17 years old
Input Posterior anterior (PA) hand radiograph
Input format DICOM
Output Greulich & Pyle bone age, standard deviation
Output format DICOM-encapsulated report
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

Regulatory

Certification
CE
Certified, Class IIa , MDR
FDA No or not yet
Intended Use Statements
Intended use (according to CE) BoneView Bone Age is a software using deep learning techniques intended to provide preliminary data for helping clinicians’ diagnosis of X-ray radiographs.

Market

Market presence
On market since 03-2023
Distribution channels AGFA, Aidoc, Blackford, deepc OS, Incepto, Sectra, Eureka Clinical AI
Countries present (clinical, non-research use) >15
Paying clinical customers (institutes) >80
Research/test users (institutes)
Pricing
Pricing model Subscription
Based on Number of analyses

Evidence

Evidence
Peer reviewed papers on performance

  • High performance for bone age estimation with an artificial intelligence solution (read)

Non-peer reviewed papers on performance
Other relevant papers