Classification of Endoscopic Image Based on Texture and Neural Network
NANYANG TECHNOLOGICAL UNIV (SINGAPORE)
Pagination or Media Count:
Computerized processing of medical images can ease the search of the representative features in the images. The endoscopic images possess rich information expressed by texture. Regions affected by diseases, such as ulcer or coli, may have different texture features. The texture model implemented in this study is Local Binary Pattern LBP and a log-likelihood ratio, called the G-statistic, is used to evaluate the similarity of regions based on LBP.
- Medicine and Medical Research
- Optical Detection and Detectors