Name
Abstract | ||
|---|---|---|
Computerised processing of medical images can ease the search of the representative features in the images. The endoscopic images possess rich information expressed by texture and regions affected by diseases, such as ulcer or coli, may have different texture features. In this paper schemes have been developed to extract features from the texture spectra in the chromatic and achromatic domains for a selected region of interest from each colour component histogram of images acquired by the M2A Swallowable Imaging Capsule. The implementation of neural network schemes and the concept of fusion of multiple classifiers have been also adopted in this paper. The preliminary test results support the feasibility of the proposed method. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.engappai.2006.09.006 | Eng. Appl. of AI |
Keywords | Field | DocType |
colour component histogram,computerised processing,texture spectrum,capsule endoscopy,soft-computing methodology,endoscopic image,medical image,multiple classifier,different texture feature,achromatic domain,m2a swallowable imaging capsule,paper scheme,feature extraction,fuzzy systems,fusion,region of interest,texture,soft computing,fuzzy system,image fusion,neural network | Histogram,Computer vision,Chromatic scale,Computer science,Computer-aided diagnosis,Feature extraction,Achromatic lens,Artificial intelligence,Soft computing,Region of interest,Artificial neural network | Journal |
Volume | Issue | ISSN |
20 | 4 | Engineering Applications of Artificial Intelligence |
Citations | PageRank | References |
12 | 0.86 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vassilis S. Kodogiannis | 1 | 272 | 35.17 |
| M. Boulougoura | 2 | 29 | 2.02 |
| E. Wadge | 3 | 12 | 1.54 |
| J. N. Lygouras | 4 | 53 | 5.33 |