Name
Title | ||
|---|---|---|
A comparison of wavelet, ridgelet, and curvelet-based texture classification algorithms in computed tomography. |
Abstract | ||
|---|---|---|
The research presented in this article is aimed at the development of an automated imaging system for classification of normal tissues in medical images obtained from computed tomography (CT) scans. This article focuses on comparing the discriminating power of several multi-resolution texture analysis techniques using wavelet, ridgelet, and curvelet-based texture descriptors. The approach consists of two steps: automatic extraction of the most discriminative texture features of regions of interest and creation of a classifier that automatically identifies the various tissues. The algorithms are extensively tested and results are compared with standard texture classification algorithms. Tests indicate that using curvelet-based texture features significantly improves the classification of normal tissues in CT scans. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.compbiomed.2006.08.002 | Comp. in Bio. and Med. |
Keywords | DocType | Volume |
automated imaging system,computed tomography,automatic extraction,curvelet-based texture descriptors,curvelet-based texture classification algorithm,normal tissue,multi-resolution texture analysis technique,medical image,standard texture classification algorithm,curvelet-based texture,discriminative texture feature | Journal | 37 |
Issue | ISSN | Citations |
4 | 0010-4825 | 41 |
PageRank | References | Authors |
1.84 | 10 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lucia Dettori | 1 | 118 | 13.13 |
| Lindsay Semler | 2 | 71 | 4.87 |