Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6920361 | Computerized Medical Imaging and Graphics | 2013 | 16 Pages |
Abstract
This paper surveys the state-of-the-art of automatic extraction of anatomical features from retinal images to assist early diagnosis of the Glaucoma. We have conducted critical evaluation of the existing automatic extraction methods based on features including Optic Cup to Disc Ratio (CDR), Retinal Nerve Fibre Layer (RNFL), Peripapillary Atrophy (PPA), Neuroretinal Rim Notching, Vasculature Shift, etc., which adds value on efficient feature extraction related to Glaucoma diagnosis.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Muhammad Salman Haleem, Liangxiu Han, Jano van Hemert, Baihua Li,