Title: ATP-MLSM: angular texture pattern-multi-level set model-based retinal image segmentation approach

Authors: Arti Taneja; Priya Ranjan; Amit Ujlayan

Addresses: Amity Institute of Information Technology, Amity University, Noida, Uttar Pradesh 201303, India ' Amity Institute of Information Technology, Amity University, Noida, Uttar Pradesh 201303, India ' Department of Mathematics, Gautam Budha University, Greater Noida, India

Abstract: This paper proposes an Angular Texture Pattern (ATP)-Multi-Level Set Model (MLSM)-based retinal image segmentation approach. The location of Optical Disk (OD) is estimated by initially collecting the blood vessel region from the retinal image. Based on the identification of OD location, the bright pixel values are estimated to provide the boundary detail of OD. From this boundary detail, the Region of Interest (ROI) such as Hard Exudates (HE) is obtained in the binary form, to enable contour formation for the OD and HE. Then, the cup-to-disk ratio of the OD is calculated, and the number of HEs is counted. The severity level of the DR and Glaucoma is determined based on the cup-to-disk ratio of the OD and HE count value. The proposed algorithm is tested by using the retinal images of the DIARETDB1 and MESSIDOR database. The proposed approach achieves better performance than the existing OD segmentation methodologies.

Keywords: ATP; angular texture patterns; diabetic retinopathy; glaucoma; MLSM; multi-level set model; optical disk; retinal images; image segmentation; blood vessel region; hard exudates; contour formation; cup-to-disk ratio; image processing.

DOI: 10.1504/IJBET.2016.081218

International Journal of Biomedical Engineering and Technology, 2016 Vol.22 No.4, pp.285 - 313

Received: 23 Nov 2015
Accepted: 17 Feb 2016
Published online: 29 Dec 2016 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article