Literature Review on Artificial Intelligence Methods for Glaucoma Screening, Segmentation, and Classification
Journal
Journal of Imaging
Date Issued
2022-01-20
Author(s)
Camara, José
Neto, Alexandre
Pires, Ivan Miguel
Villasana, María Vanessa
Cunha, António
Abstract
Artificial intelligence techniques are now being applied in different medical solutions ranging from disease screening to activity recognition and computer-aided diagnosis. The combination
of computer science methods and medical knowledge facilitates and improves the accuracy of the
different processes and tools. Inspired by these advances, this paper performs a literature review
focused on state-of-the-art glaucoma screening, segmentation, and classification based on images of
the papilla and excavation using deep learning techniques. These techniques have been shown to
have high sensitivity and specificity in glaucoma screening based on papilla and excavation images.
The automatic segmentation of the contours of the optic disc and the excavation then allows the
identification and assessment of the glaucomatous disease’s progression. As a result, we verified
whether deep learning techniques may be helpful in performing accurate and low-cost measurements
related to glaucoma, which may promote patient empowerment and help medical doctors better
monitor patients.
of computer science methods and medical knowledge facilitates and improves the accuracy of the
different processes and tools. Inspired by these advances, this paper performs a literature review
focused on state-of-the-art glaucoma screening, segmentation, and classification based on images of
the papilla and excavation using deep learning techniques. These techniques have been shown to
have high sensitivity and specificity in glaucoma screening based on papilla and excavation images.
The automatic segmentation of the contours of the optic disc and the excavation then allows the
identification and assessment of the glaucomatous disease’s progression. As a result, we verified
whether deep learning techniques may be helpful in performing accurate and low-cost measurements
related to glaucoma, which may promote patient empowerment and help medical doctors better
monitor patients.
Subjects
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