Document Detail

Coronary artery segmentation and skeletonization based on competing fuzzy connectedness tree.
MedLine Citation:
PMID:  18051073     Owner:  NLM     Status:  MEDLINE    
We propose a new segmentation algorithm based on competing fuzzy connectedness theory, which is then used for visualizing coronary arteries in 3D CT angiography (CTA) images. The major difference compared to other fuzzy connectedness algorithms is that an additional data structure, the connectedness tree, is constructed at the same time as the seeds propagate. In preliminary evaluations, accurate result have been achieved with very limited user interaction. In addition to improving computational speed and segmentation results, the fuzzy connectedness tree algorithm also includes automated extraction of the vessel centerlines, which is a promising approach for creating curved plane reformat (CPR) images along arteries' long axes.
Chunliang Wang; Orjan Smedby
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  10     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2007  
Date Detail:
Created Date:  2007-12-04     Completed Date:  2008-01-03     Revised Date:  2009-12-11    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  311-8     Citation Subset:  IM    
CMIV, Linköping University Hospital, SE-58185 Linköping, Sweden.
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MeSH Terms
Artificial Intelligence*
Computer Simulation
Coronary Angiography / methods*
Fuzzy Logic*
Imaging, Three-Dimensional / methods
Models, Cardiovascular
Pattern Recognition, Automated / methods*
Radiographic Image Enhancement / methods*
Radiographic Image Interpretation, Computer-Assisted / methods*
Reproducibility of Results
Sensitivity and Specificity
Tomography, X-Ray Computed / methods*

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

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