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Soft Computing
Erschienen in: Soft Computing 4/2021

07.10.2020 | Methodologies and Application

BAT optimization based Retinal artery vein classification

verfasst von: V. Sathananthavathi, G. Indumathi

Erschienen in: Soft Computing | Ausgabe 4/2021

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Abstract

The investigation of artery vein changes over time is considered to be the significant diagnosis process of retinal diseases like diabetic retinopathy. The diagnosis includes the characteristics analysis of artery vein vessels, changes in its tortuosity level and artery vein ratio; hence, it is important to classify the artery and vein in a better way. Computer-aided diagnosis requires the automated classification of retinal artery and vein for diagnosing the progression of diseases. In this paper, a supervised classification with Bat algorithm is proposed to discriminate the artery and vein vessels in the retinal fundus images. A novel feature vector space, including both additive colour space as well as luminous chromaticity model colour space, is constructed. BAT algorithm is applied to select the feature group which improve the classification accuracy and also to reduce the dimensionality of feature space. The proposed method is developed and analyzed using the publicly available databases DRIVE, IOSTAR and STARE.
Vorheriger Artikel Toward soft real-time stress detection using wrist-worn devices for human workspaces
Nächster Artikel A novel global harmony search algorithm for solving numerical optimizations

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Metadaten
Titel
BAT optimization based Retinal artery vein classification
verfasst von
V. Sathananthavathi
G. Indumathi
Publikationsdatum
07.10.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 4/2021
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-020-05339-z

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