Name
Title | ||
|---|---|---|
Matching colonic polyps from prone and supine CT colonography scans based on statistical curvature information |
Abstract | ||
|---|---|---|
Computed tomographic colonography (CTC) provides a feasible way for the detection of colorectal polyps and cancer screening. In the clinical practice of CTC, a true colonic polyp will be confirmed with high confidence if a radiologist can find it in both the supine and prone scans. To assist radiologists in CTC reading, we propose a new colonic polyp matching method based on statistical curvature information of polyp candidates. We first extract histograms of curvature-related features (HCF) from each polyp candidate, then use diffusion map to embed the original high dimensional data into a low-dimensional space. Experimental results show that by using our HCF method, we can improve the sensitivity from 0.58 to 0.74 at false positive rate 0.1 compared with a traditional method that uses only means of curvature-related features. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICPR.2008.4760992 | ICPR |
Keywords | Field | DocType |
computerised tomography,image matching,statistical curvature information,computed tomographic colonography scans,cancer,feature extraction,diffusion map,cancer screening,object detection,curvature-related features,colonic polyp matching method,colorectal polyp detection,medical image processing,shape,false positive rate,high dimensional data,histograms,computed tomography,current transformers | Computer vision,Histogram,False positive rate,Curvature,Computer science,Clinical Practice,Colonic Polyp,Computed Tomographic Colonography,Artificial intelligence,Cancer screening,Supine position | Conference |
ISSN | ISBN | Citations |
1051-4651 E-ISBN : 978-1-4244-2175-6 | 978-1-4244-2175-6 | 0 |
PageRank | References | Authors |
0.34 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shijun Wang | 1 | 239 | 22.83 |
| Jianhua Yao | 2 | 1135 | 110.49 |
| Ronald M. Summers | 3 | 893 | 86.16 |