Vessel Segmentation in Retinal Images using Multiscale Image Enhancement and Clustering

YAVUZ Z., KÖSE C.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Türkiye, 16 - 19 Mayıs 2015, ss.581-584 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2015.7129891
  • Basıldığı Şehir: Malatya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.581-584
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

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.