TY  - CONF
KW  - Diagnosis; Eye protection; Image processing; Optical data processing; Support vector machines; Tomography
KW  -  Glaucoma; Level Set; Local binary pattern (LBP); Optic cups; Optic disc; Retinal fundus images
KW  -  Ophthalmology
ID  - scholars9661
TI  - Glaucoma Screening Through Level Set for Optic Disc Segmentation and Textural Features for Classification
N1  - cited By 0; Conference of 7th International Conference on Intelligent and Advanced System, ICIAS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:143005
N2  - Glaucoma is considered as world's second biggest health emergency of this century. Glaucoma is an irremediable chronic ocular disease. In Glaucoma, Optic Nerve Head (ONH) gets damaged due to loss of ganglion cells. This damage of ONH causes cupping of nerve head and optic cup size increases with respect to the size of optic disc. These changes in ONH can be detected using various image processing methods which can be applied on retinal images acquired using Optical Coherence Tomograph, Retinal fundus camera and Heidelberg Retina Tomograph. This paper proposes an approach to detect Glaucoma automatically from retinal fundus images. A level set based approach for segmentation of optic disc (OD) is used and further analysis of segmented OD is done by textural information. In this approach, image features are obtained by the use of Local Binary Pattern (LBP) and these image features were classified using Support Vector Machine(SVM) classifier. © 2018 IEEE.
AV  - none
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059755517&doi=10.1109%2fICIAS.2018.8540615&partnerID=40&md5=bae4031b6bec82c22319c6641c3e7f4e
A1  - Joshi, A.
A1  - Kadethankar, A.
A1  - Patwardhan, V.
A1  - Porwal, P.
A1  - Pachade, S.
A1  - Kokare, M.
A1  - Meriaudeau, F.
SN  - 9781538672693
PB  - Institute of Electrical and Electronics Engineers Inc.
Y1  - 2018///
ER  -