VUNO Med®-BoneAge™

VUNO
It assists bone age assessment based on a child’s hand X-ray image. A customized report of bone age assessment is automatically generated.
Information source: Vendor
Last updated: Jan. 15, 2024

General Information

General
Product name VUNO Med®-BoneAge™
Company VUNO
Subspeciality MSK
Modality X-ray
Disease targeted Growth disorder, short stature, tall stature, early or late puberty, congenital adrenal hyperplasia
Key-features Bone age assessment, Automatic report generation
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion

Technical Specifications

Data characteristics
Population Patients under 19 years old
Input Hand bone X-ray image
Input format DICOM
Output Estimated bone age
Output format DICOM, PDF
Technology
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone third party application, Stand-alone webbased
Deployment Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based, Hybrid solution
Trigger for analysis Automatically, right after the image acquisition
Processing time < 3 sec

Regulatory

Certification
CE
Certified, Class IIa , MDD
FDA No or not yet
Intended Use Statements
Intended use (according to CE)

Market

Market presence
On market since 05-2018
Distribution channels
Countries present (clinical, non-research use) 10+
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model Pay-per-use
Based on Number of analyses

Evidence

Evidence
Peer reviewed papers on performance

  • Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction (read)

  • Computerized Bone Age Estimation Using Deep Learning Based Program: Evaluation of the Accuracy and Efficiency (read)

Non-peer reviewed papers on performance A Comparative Study of Automatic Hand Bone Age Assessment Systems, RSNA 2017
Other relevant papers