Anterior Segment Measurement Dataset Using Ultrasound Biomicroscopy Image Analysis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Purpose: The purpose of this study was to provide a comprehensive, quantitative dataset of anterior segment (AS) parameters obtained from ultrasound biomicroscopy (UBM) images to support research in ocular development, disease characterization, and image-based analysis. Methods: UBM images were prospectively collected from 185 eyes of 138 participants aged 3 weeks to 26 years (median = 17 months), encompassing diagnoses such as healthy controls, primary congenital glaucoma (PCG), glaucoma following cataract surgery (GFCS), congenital cataract, traumatic cataract, Lowe syndrome, and Sturge-Weber syndrome (SWS)-associated glaucoma. Twenty-seven quantitative AS parameters were measured from deidentified images using ImageJ software following a standardized protocol. Results: The resulting dataset includes demographic and diagnostic metadata paired with quantitative UBM-derived parameters for each eye. The dataset is provided in comma-separated value (CSV) format with an accompanying data dictionary. Conclusions: This dataset provides one of the most extensive collections of quantitative pediatric AS measurements obtained by UBM, enabling characterization of age- and disease-related anatomic variation and facilitating reproducible secondary analyses. Translational Relevance: This open-source pediatric UBM dataset establishes a foundation for studies of ocular growth, disease mechanisms, and surgical planning, and provides a valuable resource for the development and validation of automated image analysis and machine learning models in pediatric AS imaging.
DOI: 10.1167/tvst.15.8.19
Language: English
Subfield: Ophthalmology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,850
Funder: National Institutes of Health
OpenAlex ID: W7204102969