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akaturk Akademik ölçüm

Makale detayı · 2017

Comparison of Unsupervised Segmentation of Retinal Blood Vessels in Gray Level Image with PCA and Green Channel Image

International Journal of Intelligent Systems and Applications in Engineering (IJISAE)

YÖKSİS OpenAlex Açık erişim · diamond SJR Q4 TR Index Atıf 4 Yüzdelik 59.1% FWCI 0.2
Yıl
2017
ISSN
2147-6799
Tür
article

Veri kaynağı ayrımı

  • YÖKSİS YÖKSİS makale kaydı
  • OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)

Özet

İngilizce (OpenAlex)

In this study, an unsupervised retina blood vessel segmentation process was performed on the gray level images with PCA and the green channel of the RGB image, which most clearly shows retinal vessels and the results were compared. The average accuracy rate obtained for the gray level image with PCA after the study was 0,9443, while the average accuracy rate obtained for the green channel was 0,9685. The study was performed using 40 images in the DRIVE data set which is one of the most common retina data sets known.

Konular

  • Retinal Imaging and Analysis

Birincil konu Retinal Imaging and Analysis

Yazarlar

  1. ESRA KAYA SELÇUK ÜNİVERSİTESİ
  2. İSMAİL SARITAŞ SELÇUK ÜNİVERSİTESİ
  3. MURAT CEYLAN KONYA TEKNİK ÜNİVERSİTESİ