Affiliations:
Department of Computer Science and Engineering, Amrita University, Bengaluru, India
Correspondence:
[*]
Corresponding author. Nilima Kulkarni, Department of Computer Science and Engineering, Amrita University, Bengaluru, India. E-mail: [email protected].
Abstract: Optic disc (OD) detection is an important step in a number of algorithms developed for automatic extraction of anatomical structures and retinal lesions. In this article, a novel system, eye gaze– based OD detection, is presented for detecting OD in fundus retinal image using the knowledge developed from the expert’s eye gaze data. The eye gaze data are collected from expert optometrists and non-experts group while viewing the fundus retinal images. The task given to them is to spot the OD in fundus retinal images. Eye gaze fixations were used to identify the target and distractor regions. The image-based features were extracted from the identified regions. The top-down (TD) knowledge is developed using feature ranking and fuzzy system. This TD knowledge is further used for building the TD map. The success rates for various standard datasets are: DRIVE dataset, 100%; DRIONS-DB, 98.2%; INSPIRE, 97.5%; High Resolution Fundus Images, 100%; DIRECTDB0, 96.9%; ONHSD, 91.9% and STARE, 81.4%.
