Paper Info
Title
Blood vessel extraction from retinal images using Complex Wavelet Transform and Complex-Valued Artificial Neural Network.
Abstract
Retinal imaging in ophthalmology plays an important role for the diagnosis of diabetes, cardiovascular disease, etc. In retina images, changes of blood vessels can help the expert to detection of diseases. Manually extraction of blood vessels from retinal images is usually difficult process due to depending on the experience of physician, back-ground artifacts, different acquisition process. Therefore, the aim of this study is to purpose a novel method for automatic blood vessel extraction from retinal image. This study presents a combined structure. This structure is realized with two cascade stages: feature extraction with 4th level Complex Wavelet Transform (CWT) and Complex-Valued Artificial Neural Networks (CVANN) for the blood vessels segmentation. To check the validation of proposed method, public DRIVE database is used. Result of this study has a higher accuracy (98.56 %) than previously studies in the literature.
Year
DOI
Venue
2013
10.1109/TSP.2013.6614053
TSP
Keywords
DocType
Citations 
blood vessels,eye,feature extraction,medical image processing,neural nets,wavelet transforms,automatic blood vessel extraction,blood vessels segmentation,complex valued artificial neural networks,feature extraction,fourth level complex wavelet transform,ophthalmology,public DRIVE database,retinal image,retinal imaging,Blood vessel extraction,complex wavelet transform,complex-valued artificial neural network,retinal image
Conference
6
PageRank 
References 
Authors
0.45
5
2
Name
Order
Citations
PageRank
Murat Ceylan1808.37
Hüseyin Yasar2111.89