DocumentCode
2560284
Title
CNN-based automatic retinal vascular tree extraction
Author
Alonso-Montes, C. ; Vilariño, D.L. ; Penedo, M.G.
Author_Institution
Dept. of Comput. Sci., Coruna Univ., Spain
fYear
2005
fDate
28-30 May 2005
Firstpage
61
Lastpage
64
Abstract
The retinal vascular tree has become an important task of medical image processing in different scientific areas. Many studies have focused on developing an automatic algorithm, however little attention has been paid to improve computational processing time of these algorithms. In this paper, an automatic methodology for retinal vascular tree extraction using cellular neural networks (CNNs) is proposed. The aim of using CNNs is to improve computational time in order to achieve real-time requirements.
Keywords
blood vessels; cellular neural nets; eye; medical image processing; CNN-based automatic retinal vascular tree extraction; cellular neural networks; medical image processing; Active contours; Angiography; Biomedical image processing; Biomedical imaging; Cellular neural networks; Computer architecture; Computer science; Histograms; Image segmentation; Retina;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
Print_ISBN
0-7803-9185-3
Type
conf
DOI
10.1109/CNNA.2005.1543161
Filename
1543161
Link To Document