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- Title
Multiple Preprocessing Hybrid Level Set Model for Optic Disc Segmentation in Fundus Images.
- Authors
Xue, Xiaozhong; Wang, Linni; Du, Weiwei; Fujiwara, Yusuke; Peng, Yahui
- Abstract
The accurate segmentation of the optic disc (OD) in fundus images is a crucial step for the analysis of many retinal diseases. However, because of problems such as vascular occlusion, parapapillary atrophy (PPA), and low contrast, accurate OD segmentation is still a challenging task. Therefore, this paper proposes a multiple preprocessing hybrid level set model (HLSM) based on area and shape for OD segmentation. The area-based term represents the difference of average pixel values between the inside and outside of a contour, while the shape-based term measures the distance between a prior shape model and the contour. The average intersection over union (IoU) of the proposed method was 0.9275, and the average four-side evaluation (FSE) was 4.6426 on a public dataset with narrow-angle fundus images. The IoU was 0.8179 and the average FSE was 3.5946 on a wide-angle fundus image dataset compiled from a hospital. The results indicate that the proposed multiple preprocessing HLSM is effective in OD segmentation.
- Subjects
OPTIC disc; IMAGE segmentation; RETINAL diseases; PIXELS
- Publication
Sensors (14248220), 2022, Vol 22, Issue 18, p6899
- ISSN
1424-8220
- Publication type
Article
- DOI
10.3390/s22186899