Title :
Vessel segmentation in retinal images using multiscale image enhancement and clustering
Author :
Yavuz, Zafer ; Kose, Cemal
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey
Abstract :
Some diseases in human body such as diabet could be affect the morphology of the retina. The diagnosis and treatment of these diseases can be made easily by improved computerized techniques. Retinal blood vessel segmentation phase is an important step for diagnosis and treatment. Blood vessel segmentation in color retinal fundus images is employeed in this paper. First, a preprocessing step is performed and then multiscale Frangi filter is applied in order to enhance blood vessels. Afterwards Fuzzy C-means clustering method is used to obtain binary vessel image. Finally, a postprocessing step is performed to increase performance.We use two publicly available retinal fundus image databases STARE and DRIVE to measure the performance of the system. As a result we get 95.95% of accuracy for STARE database and 95.95% of accuracy for DRIVE database.
Keywords :
blood vessels; image colour analysis; image enhancement; image segmentation; patient diagnosis; patient treatment; DRIVE database; STARE database; color retinal fundus images; disease; fuzzy C-means clustering; multiscale Frangi filter; multiscale image clustering; multiscale image enhancement; patient diagnosis; patient treatment; retinal blood vessel segmentation; retinal images; Accuracy; Biomedical imaging; Blood vessels; Image enhancement; Image segmentation; Retina; Fuzzy C-means clustering; clustering; frangi filter; image enhancement; multiscale vessel segmentation; retinal fundus image;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7129891