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Anterior Segment Measurement Dataset Using Ultrasound Biomicroscopy Image Analysis
Taylor Kolosky1, He Eun Forbes2, Moran R Levin3
1University of Maryland School of Medicine, Baltimore, MD, USA.
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.
