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Article overview
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Deep Retinal Image Understanding | | Kevis-Kokitsi Maninis
; Jordi Pont-Tuset
; Pablo Arbeláez
; Luc Van Gool
; | | Date: |
5 Sep 2016 | | Abstract: | This paper presents Deep Retinal Image Understanding (DRIU), a unified
framework of retinal image analysis that provides both retinal vessel and optic
disc segmentation. We make use of deep Convolutional Neural Networks (CNNs),
which have proven revolutionary in other fields of computer vision such as
object detection and image classification, and we bring their power to the
study of eye fundus images. DRIU uses a base network architecture on which two
set of specialized layers are trained to solve both the retinal vessel and
optic disc segmentation. We present experimental validation, both qualitative
and quantitative, in four public datasets for these tasks. In all of them, DRIU
presents super-human performance, that is, it shows results more consistent
with a gold standard than a second human annotator used as control. | | Source: | arXiv, 1609.1103 | | Services: | Forum | Review | PDF | Favorites | |
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