Anterior Segment Measurement Dataset Using Ultrasound Biomicroscopy Image Analysis.

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.