Name
Title | ||
|---|---|---|
Hierarchical part-based detection of 3D flexible tubes: application to CT colonoscopy. |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11866763_57 | MICCAI (2) |
Keywords | Field | DocType |
tube detection rate,ct colonoscopy,rectal tube,flexible tube,hierarchical part-based detection,current polyp detection algorithm,tube cross section,tube segment,false alarm,dynamic programming algorithm,whole flexible tube,learning-based method,cross section | Computer vision,Dynamic programming,Colonoscopy,False alarm,Pattern recognition,Computer science,Segmentation,Manual annotation,Artificial intelligence,Constant false alarm rate,Rectal Tube | Conference |
Volume | Issue | ISSN |
9 | Pt 2 | 0302-9743 |
ISBN | Citations | PageRank |
3-540-44727-X | 3 | 0.52 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adrian Barbu | 1 | 768 | 58.59 |
| Luca Bogoni | 2 | 616 | 65.11 |
| Dorin Comaniciu | 3 | 8389 | 601.83 |