학술논문

Optic cup segmentation based on extracting blood vessel kinks and cup thresholding using Type-II fuzzy approach
Document Type
Conference
Source
2015 2nd International Conference on Opto-Electronics and Applied Optics (IEM OPTRONIX) Opto-Electronics and Applied Optics (IEM OPTRONIX), 2015 2nd International Conference on. :1-3 Oct, 2015
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Image segmentation
Biomedical imaging
Blood vessels
Optical imaging
Retina
Transforms
Databases
optic cup
blood vessels
top hat transform
Otsu's function
Interval Type-II fuzzy entropy
glaucoma
Language
Abstract
A novel technique has been developed to segment the optic cup from a 2D colored fundus image. Cup segmentation is the most challenging part of image processing the optic nerve head (ONH) due to the complexity of its structure. The cup size is used for diagnosis of glaucoma. Blood vessels densely cover the cup boundary in some cases and in other cases, they form the boundaries. Therefore, extracting the vessels were conducted by using a top hat transform and Otsu's function in order to detect the curvature of the blood vessels (kinks), which indicates the cup boundary. Then, an Interval Type-II fuzzy entropy procedure was applied to cup thresholding. Finally, the Hough transform was applied to approximate the cup boundaries. The algorithm was evaluated on 100 fundus images from the RIGA database, where the cup was manually marked by 6 Ophthalmologists. The cup detection accuracy was 72.5%.