An improved gradient vector flow algorithm for optic disc segmentation

• Published in: 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Vol. 2010; pp. 4793 - 4796
• Main Authors: Huiyu Zhou, Schaefer, Gerald, Tangwei Liu, Faquan Lin
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2010
• Subjects: Adult; Aged; Aged, 80 and over; Algorithms; Biomedical optical imaging; Diabetic Retinopathy - pathology; Female; Force; Humans; Image edge detection; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image segmentation; Male; Middle Aged; Optic Disk - pathology; Optical imaging; Pattern Recognition, Automated - methods; Reproducibility of Results; Retina; Retinoscopy - methods; Sensitivity and Specificity; Subtraction Technique
• ISBN: 1424441234; 9781424441235
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/IEMBS.2010.5628025

The optic disc provides important cues for accurate diagnosis of various retinopathic diseases. Accurate segmentation of the optic disc is therefore an important step in the analysis of retinal images. Gradient vector flow (GVF) based segmentation algorithms have been used successfully on a variety of medical imagery, however, due to the compromise of internal and external energy forces, it can lead to less accurate segmentation in certain cases. In this paper, we show, that through incorporation of a mean shift term into the GVF framework, improved segmentation accuracy can be achieved. Experimental results on a large dataset of retinal images demonstrate that the presented method reliably detects the border of the optic disc.