Document Detail


Hierarchical part-based detection of 3D flexible tubes: application to CT colonoscopy.
MedLine Citation:
PMID:  17354805     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
In this paper, we present a learning-based method for the detection and segmentation of 3D free-form tubular structures, such as the rectal tubes in CT colonoscopy. This method can be used to reduce the false alarms introduced by rectal tubes in current polyp detection algorithms. The method is hierarchical, detecting parts of the tube in increasing order of complexity, from tube cross sections and tube segments to the whole flexible tube. To increase the speed of the algorithm, candidate parts are generated using a voting strategy. The detected tube segments are combined into a flexible tube using a dynamic programming algorithm. Testing the algorithm on 210 unseen datasets resulted in a tube detection rate of 94.7% and 0.12 false alarms per volume. The method can be easily retrained to detect and segment other tubular 3D structures.
Authors:
Adrian Barbu; Luca Bogoni; Dorin Comaniciu
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Publication Detail:
Type:  Evaluation Studies; Journal Article    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  9     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2006  
Date Detail:
Created Date:  2007-03-14     Completed Date:  2007-04-06     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:  462-70     Citation Subset:  IM    
Affiliation:
Siemens Corporate Research, Princeton, NJ, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Artifacts*
Artificial Intelligence
Colonography, Computed Tomographic / methods*
Humans
Imaging, Three-Dimensional / methods*
Information Storage and Retrieval / methods
Pattern Recognition, Automated / methods*
Prostheses and Implants*
Radiographic Image Enhancement / methods*
Radiographic Image Interpretation, Computer-Assisted / methods*
Rectum / radiography
Reproducibility of Results
Sensitivity and Specificity
Subtraction Technique

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


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