Digital pathology is expanding the possibilities for studying ocular tissues and disease mechanisms through high-resolution digital imaging and computational analysis. The digitization of pathological specimens enables researchers to examine tissue characteristics systematically while creating datasets that can be integrated with artificial intelligence and other analytical technologies.
This session will explore digital pathology applications in ocular oncology, corneal disorders, retinal pathology, inflammatory diseases, and other ophthalmic conditions. Discussions will focus on digital image analysis, automated tissue classification, computational pathology, biomarker identification, and integration of pathological findings with clinical and imaging data.
The session will also address challenges related to image standardization, data management, validation, and interpretation. Researchers will examine how digital pathology and computational methods can strengthen ophthalmic research and contribute to improved understanding, diagnosis, and characterization of ocular diseases.