Computational Ophthalmology: From Pixels to Predictions – Hardcover

This book provides a comprehensive and practice-oriented account of Computational Ophthalmology, an emerging discipline that applies computational methods-including artificial intelligence, machine learning, quantitative imaging, and data-driven modeling-to ophthalmic diagnosis, prognosis, and clinical decision-making.

The scope of the book spans major ophthalmic subspecialties, with a particular focus on retinal diseases, glaucoma, corneal and ocular surface disorders, inherited retinal diseases, and neuro-ophthalmology. Core topics include quantitative image-derived biomarkers from OCT, OCT angiography, fundus imaging, and visual fields; algorithm development and validation; explainable AI; integration of multimodal data (imaging, clinical, genetic, and functional); and the role of computational models in disease staging, progression prediction, and treatment response assessment. Regulatory considerations, ethical frameworks, and limitations of current computational approaches are addressed alongside technical advances. Through structured case studies, validated use cases, and evidence-graded examples, the book aims to serve as both a clinical reference and a strategic guide for integrating computational tools into ophthalmic practice, research, and clinical trials, supporting the transition from descriptive imaging to data-driven, precision ophthalmology.

Written for practicing ophthalmologists, clinician-scientists, biomedical engineers, and industry professionals, the book translates advances in computational science into clinically meaningful tools, enabling ophthalmologists and vision scientists to understand, evaluate, and responsibly apply computational outputs in real-world patient care. Discussion questions, Q&A’s, and prompts are included throughout the book, making it an ideal resource for those studying ophthalmology, developing their skills, and studying advancements in the field.