TY - GEN
T1 - Sector-based optic cup segmentation with intensity and blood vessel priors
AU - Yin, Fengshou
AU - Liu, Jiang
AU - Wong, Damon W.K.
AU - Tan, Ngan Meng
AU - Cheng, Jun
AU - Cheng, Ching Yu
AU - Tham, Yih Chung
AU - Wong, Tien Yin
PY - 2012
Y1 - 2012
N2 - The optic cup segmentation is critical for automated cup-to-disk ratio measurement, and hence computer-aided diagnosis of glaucoma. In this paper, we propose a novel sector-based method for optic cup segmentation. The method comprises two parts: intensity-based cup segmentation with shape constraints and blood vessel-based refinement. The initial estimation of the cup is obtained by applying a statistical deformable model on the vessel free image. At the same time, blood vessels within the optic disk are extracted, after which vessel bendings and vessel boundaries in the nasal side are located. Subsequently, these key points in the blood vessels are used to fine tune the cup. The algorithm is evaluated on 650 fundus images from the ORIGA-light database. Experimental results show that the Dice coefficient for the optic cup segmentation can be as high as 0.83, which outperforms other existing methods. The results demonstrate good potential for the proposed method to be used in automated optic cup segmentation and glaucoma diagnosis.
AB - The optic cup segmentation is critical for automated cup-to-disk ratio measurement, and hence computer-aided diagnosis of glaucoma. In this paper, we propose a novel sector-based method for optic cup segmentation. The method comprises two parts: intensity-based cup segmentation with shape constraints and blood vessel-based refinement. The initial estimation of the cup is obtained by applying a statistical deformable model on the vessel free image. At the same time, blood vessels within the optic disk are extracted, after which vessel bendings and vessel boundaries in the nasal side are located. Subsequently, these key points in the blood vessels are used to fine tune the cup. The algorithm is evaluated on 650 fundus images from the ORIGA-light database. Experimental results show that the Dice coefficient for the optic cup segmentation can be as high as 0.83, which outperforms other existing methods. The results demonstrate good potential for the proposed method to be used in automated optic cup segmentation and glaucoma diagnosis.
UR - http://www.scopus.com/inward/record.url?scp=84881467872&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2012.6346214
DO - 10.1109/EMBC.2012.6346214
M3 - Conference contribution
C2 - 23366175
AN - SCOPUS:84881467872
SN - 9781424441198
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 1454
EP - 1457
BT - 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
T2 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Y2 - 28 August 2012 through 1 September 2012
ER -