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Bone age assessment of children using a digital hand atlas
Arkadiusz Gertych1, Aifeng Zhang, James Sayre
1Image Processing and Informatics Laboratory, Department of Radiology, University of Southern California, 4676 Admiralty Way, Suite 601, Marina del Rey, CA 90292, USA. gertych@usc.edu
Insights
This study introduces an automated bone age assessment tool for children using a digital hand atlas and computer-assisted diagnosis (CAD). The system analyzes radiographs to determine bone age, aiding pediatric diagnostics.
Area of Science:
- Medical Imaging
- Pediatric Radiology
- Artificial Intelligence in Healthcare
Background:
- Accurate bone age assessment is crucial for diagnosing growth disorders in children.
- Current methods can be time-consuming and subjective.
Purpose of the Study:
- To develop and validate an automated method for bone age assessment in children.
- To create a comprehensive digital hand atlas for diverse pediatric populations.
Main Methods:
- A database of 1400 digitized hand radiographs from diverse ethnic groups (Caucasian, Asian, African-American, Hispanic) and genders (male, female) aged 1-18 years was compiled.
- A computer-assisted diagnosis (CAD) module was developed, extracting features from seven regions of interest (ROIs), including carpal and phalangeal areas.
- Fuzzy classifiers were trained on these features to assess bone age across 11 categories (race/gender specific, male, female, and combined).
Main Results:
- An automated system for bone age assessment was successfully developed.
- The system utilizes a digital hand atlas and CAD module trained on a diverse dataset.
- Integration with PACS is underway for clinical validation.
Conclusions:
- The developed automated method offers a promising approach for objective and efficient bone age assessment in children.
- The digital hand atlas provides a valuable resource for research and clinical applications.
- Further validation in clinical settings is essential to confirm its utility.
Abstract:
We have developed an automated method to assess bone age of children using a digital hand atlas. The hand atlas consists of two components. The first component is a database which is comprised of a collection of 1400 digitized left hand radiographs from evenly distributed normally developed children of Caucasian (CA), Asian (AS), African-American (AA) and Hispanic (HI) origin, male (M) and female (F), ranged from 1- to 18-year-old; and relevant patient demographic data along with pediatric radiologists' readings of each radiograph. This data is separate into eight categories: CAM, CAF, AAM, AAF, HIM, HIF, ASM, and ASF. In addition, CAM, AAM, HIM, and ASM are combined as one male category; and CAF, AAF, HIF, and ASF are combined as one female category. The male and female are further combined as the F & M category. The second component is a computer-assisted diagnosis (CAD) module to assess a child bone age based on the collected data. The CAD method is derived from features extracted from seven regions of interest (ROIs): the carpal bone ROI, and six phanlangeal PROIs. The PROIs are six areas including the distal and middle regions of three middle fingers. These features were used to train the 11 category fuzzy classifiers: one for each race and gender, one for the female, one male, and one F & M, to assess the bone age of a child. The digital hand atlas is being integrated with a PACS for validation of clinical use.
