BoneXpert

Visiana

Key Features

Bone age
Bone Health Index
Percent Adult Height

General Information

Product name

BoneXpert

Company

Visiana

Subspeciality

MSK

Modality

X-ray

Disease targeted

Short stature, tall stature, early or late puberty, Congenital Adrenal Hyperplasia (CAH), orthopedic treatment planning, orthodontics, sports medicine, legal medicine, clinical trials

Main task

Not specified

Technical Specifications

Population

Children from age 0 (zero) years, all ethnicities

Patient population age

Not specified

Input

Posterior anterior (PA) hand radiograph

Input format

DICOM

Output

Annotated DICOM image, DICOM-encapsulated pdf report, Structured Report

Output format

DICOM

Integration

Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application, Support for RIS integration with DICOM Structured Reports

Deployment

Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Etc., Image upload, On demand, Right after the image acquisition, Triggered by a user through e.g. a button click

Processing time

3 - 10 seconds

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class I

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

03-2009

AI Platforms

Not specified

Resellers

Not specified

Countries present

>40

Paying clinical customers

>200

Research/test users

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Automatic Bone Age Determination in Adult Height Prediction for Girls with Early Variants Puberty and Precoccious Puberty

Peer-Reviewed

View

A comparison of two artificial intelligence-based methods for assessing bone age in Turkish children: BoneXpert and VUNO Med-Bone Age

Peer-Reviewed

View

Performance of two different artificial intelligence (AI) methods for assessing carpal bone age compared to the standard Greulich and Pyle method

Peer-Reviewed

View

Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction

Peer-Reviewed

View

An Automated Method for Determination of Bone Age

Peer-Reviewed

View

A paediatric bone index derived by automated radiogrammetry

Peer-Reviewed

View

Automated determination of bone age from hand X-rays at the end of puberty and its applicability for age estimation

Peer-Reviewed

View

Clinical application of automated Greulich-Pyle bone age determination in children with short stature

Peer-Reviewed

View

Prediction of Adult Height Based on Automated Determination of Bone Age

Peer-Reviewed

View

Validation and Reference Values of Automated Bone Age Determination for Four Ethnicities

Peer-Reviewed

View

Validation of automatic bone age rating in children with precocious and early puberty

Peer-Reviewed

View

Validation of automatic bone age determination in children with congenital adrenal hyperplasia

Peer-Reviewed

View

Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment

Peer-Reviewed

View

Accuracy and self-validation of automated bone age determination

Technical Papers

Technical

View

The RSNA Pediatric Bone Age Machine Learning Challenge, Radiology 2018