Accession Number:

ADA409511

Title:

Classification of Endoscopic Image Based on Texture and Neural Network

Descriptive Note:

Corporate Author:

NANYANG TECHNOLOGICAL UNIV (SINGAPORE)

Report Date:

2001-10-25

Pagination or Media Count:

6.0

Abstract:

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.

Subject Categories:

  • Medicine and Medical Research
  • Optical Detection and Detectors
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE