Name
Title | ||
|---|---|---|
Polyp Detection In Ct Colonography Based On Shape Characteristics And Kullback-Leibler Divergence |
Abstract | ||
|---|---|---|
As an alternative procedure to the current methods which consider only the mean values of shape features to globally characterize a candidate shape polyps, probability density functions (PDFs) of some feature variables constructed based on Gaussian and mean curvatures are used to characterize the global shape of a candidate lesion. The decision on whether or not this candidate lesion is a polyp is made by comparing the density functions of the considered shape feature variables to reference PDFs of the same variables obtained from a preconstructed polyp/non polyp data base. The Kullback-Leibler divergence is used as a dissimilarity measure to compare these PDFs and make a decision based on closeness. Experiments carried out on real data are used to illustrate the effectiveness of the proposed method in comparison to existing ones. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ISBI.2008.4541076 | 2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4 |
Keywords | Field | DocType |
image shape analysis, probability measures | Computer vision,Divergence,Pattern recognition,Probability measure,Gaussian,Computed tomography,Computed Tomographic Colonography,Artificial intelligence,Virtual colonoscopy,Probability density function,Mathematics,Kullback–Leibler divergence | Conference |
ISSN | Citations | PageRank |
1945-7928 | 3 | 0.47 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ju Lynn Ong | 1 | 31 | 4.45 |
| Abd-Krim Seghouane | 2 | 193 | 24.99 |
| Kevin Osborn | 3 | 6 | 0.85 |