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Automatic Optic Disc Segmentation Based on Modified Local Image Fitting Model with Shape Prior Information.
- Source :
- Journal of Healthcare Engineering; 3/14/2019, p1-10, 10p
- Publication Year :
- 2019
-
Abstract
- Accurate optic disc (OD) detection is an essential yet vital step for retinal disease diagnosis. In the paper, an approach for segmenting OD boundary without manpower named full-automatic double boundary extraction is designed. There are two main advantages in it. (1) Since the performances and the computational cost produced by iterations of contour evolution of active contour models- (ACM-) based approaches greatly depend on the initialization, this paper proposes an effective and adaptive initial level set contour extraction approach using saliency detection and threshold techniques. (2) In order to handle unreliable information generated by intensity in abnormal retinal images caused by diseases, a modified LIF approach is presented by incorporating the shape prior information into LIF. We test the effectiveness of the proposed approach on a publicly available DIARETDB0 database. Experimental results demonstrate that our approach outperforms well-known approaches in terms of the average overlapping ratio and accuracy rate. [ABSTRACT FROM AUTHOR]
- Subjects :
- OPTIC disc
LEVEL set methods
GEOMETRIC shapes
IMAGE segmentation
EXAMPLE
Subjects
Details
- Language :
- English
- ISSN :
- 20402295
- Database :
- Complementary Index
- Journal :
- Journal of Healthcare Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 135311421
- Full Text :
- https://doi.org/10.1155/2019/2745183