Please use this identifier to cite or link to this item:
|Title:||Automated optic disk boundary detection by modified active contour model|
|Citation:||Xu, J., Chutatape, O., Chew, P. (2007-03). Automated optic disk boundary detection by modified active contour model. IEEE Transactions on Biomedical Engineering 54 (3) : 473-482. ScholarBank@NUS Repository. https://doi.org/10.1109/TBME.2006.888831|
|Abstract:||This paper presents a novel deformable-model-based algorithm for fully automated detection of optic disk boundary in fundus images. The proposed method improves and extends the original snake (deforming-only technique) in two aspects: clustering and smoothing update. The contour points are first self-separated into edge-point group or uncertain-point group by clustering after each deformation, and these contour points are then updated by different criteria based on different groups. The updating process combines both the local and global information of the contour to achieve the balance of contour stability and accuracy. The modifications make the proposed algorithm more accurate and robust to blood vessel occlusions, noises, ill-defined edges and fuzzy contour shapes. The comparative results show that the proposed method can estimate the disk boundaries of 100 test images closer to the groundtruth, as measured by mean distance to closest point (MDCP) < 3 pixels, with the better success rate when compared to those obtained by gradient vector flow snake (GVF-snake) and modified active shape models (ASM). © 2007 IEEE.|
|Source Title:||IEEE Transactions on Biomedical Engineering|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 21, 2018
WEB OF SCIENCETM
checked on Apr 30, 2018
checked on May 10, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.