Name
Abstract | ||
|---|---|---|
In this paper, we present a novel approach to predict the histological diagnosis of colorectal lesions from high-magnification colonoscopy images by means of Pit Pattern analysis. Motivated by the shortcomings of discriminant classifier approaches, we present a generative model based strategy which is closely related to content-based image retrieval (CBIR) systems. The ingredients of the approach are the Dual-Tree Complex Wavelet Transform (DTCWT) and the mathematical construct of copulas. Our experimental study on a set of 627 images confirms, that the joint statistical model leads to impressive prediction results compared to previous work. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CVPRW.2010.5543146 | CVPR Workshops |
Field | DocType | Volume |
Computer science,Image retrieval,Artificial intelligence,Probabilistic logic,Classifier (linguistics),Wavelet transform,Computer vision,Pattern recognition,Feature extraction,Statistical model,Complex wavelet transform,Machine learning,Generative model | Conference | 2010 |
Issue | ISSN | ISBN |
1 | 2160-7508 | 978-1-4244-7029-7 |
Citations | PageRank | References |
7 | 0.71 | 16 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R Kwitt | 1 | 448 | 35.15 |
| Andreas Uhl | 2 | 1958 | 223.07 |
| M Häfner | 3 | 143 | 11.99 |
| Alfred Gangl | 4 | 69 | 4.70 |
| F Wrba | 5 | 72 | 5.10 |
| Andreas Vécsei | 6 | 167 | 18.36 |