Document Detail


A novel vessel segmentation algorithm for pathological retina images based on the divergence of vector fields.
MedLine Citation:
PMID:  18334445     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper, a method is proposed for detecting blood vessels in pathological retina images. In the proposed method, blood vessel-like objects are extracted using the Laplacian operator and noisy objects are pruned according to the centerlines, which are detected using the normalized gradient vector field. The method has been tested with all the pathological retina images in the publicly available STARE database. Experiment results show that the method can avoid detecting false vessels in pathological regions and can produce reliable results for healthy regions.
Authors:
Benson Y Lam; Hong Yan
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on medical imaging     Volume:  27     ISSN:  0278-0062     ISO Abbreviation:  IEEE Trans Med Imaging     Publication Date:  2008 Feb 
Date Detail:
Created Date:  2008-03-12     Completed Date:  2008-04-08     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8310780     Medline TA:  IEEE Trans Med Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  237-46     Citation Subset:  IM    
Affiliation:
Department of Electronic Engneering, City University of Hong Kong, Kowloon, Hong Kong. 50005347@student.cityu.edu.hk
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Cluster Analysis
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods
Pattern Recognition, Automated / methods*
Reproducibility of Results
Retinal Diseases / pathology*
Retinal Vessels / pathology*
Retinoscopy / methods*
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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