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Deep Learning for Automated Glaucoma Detection by aaryasajan is a document available to read on EtoBox.

What is Deep Learning for Automated Glaucoma Detection about?

This document presents a report on a hybrid deep learning model for automated glaucoma detection from retinal fundus images, emphasizing the integration of anatomical and geometric features for improved accuracy. The model processes fundus images through quality filtering, vessel segmentation, and neuroretinal rim thickness estimation to enhance the detection of glaucomatous damage. The report also reviews existing models and highlights the limitations of traditional diagnostic methods, advocating for the a

Author

aaryasajan

Language

EN