Euclidean Distance Based Region Selection for Fundus Images

Ramakrishnan Sundaram (), K. S. Ravichandran () and Premaladha Jayaraman ()
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Ramakrishnan Sundaram: SASTRA Deemed University, School of Computing
K. S. Ravichandran: SASTRA Deemed University, School of Computing
Premaladha Jayaraman: SASTRA Deemed University, School of Computing

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 1659-1664 from Springer

Abstract: Abstract Fundus camera captures the posterior portion of the eye. Extraction of Optic Papilla, Optic cup, Blood vessels and Macula from the captured fundus image is done by using image segmentation algorithms for diagnosis purpose. Diseases like glaucoma, diabetic retinopathy and retinoblastoma adds artefacts in the fundus images. These artefacts makes the segmentation a difficult task. When conventional segmentation algorithms are applied for the extraction of exudates, it also identifies the regions belonging to optic papilla. Even though optic papilla is a single region, the presence of optic nerve head occludes a portion of optic papilla that leads to generation of isolated regions. These isolated regions of optic papilla are false regions which have similar properties of exudates. Hence there is a need to exclude the false regions and segment the exudates for quantification which is used for diagnosing diabetic retinopathy. To achieve this objective, a region selection algorithm using Euclidean distance measure is proposed in this communication. After selecting the regions belonging to optic papilla, it is subtracted from the segmented image to retain the exudate regions. The discarded region can be used for segmenting optic papilla accurately which is an important for diagnosing glaucoma.

Keywords: Fundus image; Optic papilla; Segmentation; Euclidean distance; Region selection (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_170

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DOI: 10.1007/978-3-030-41862-5_170

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