Computer-assisted pit-pattern classification in different wavelet domains for supporting dignity assessment of colonic polyps

PATTERN RECOGNITION

卷:42

Article

Haefner, Michael²  Kwitt, Roland¹  Uhl, Andreas¹  Wrba, Friedrich³  Gangl, Alfred²  Vecsei, Andreas⁴ 

[1] Salzburg Univ, Dept Comp Sci, A-5020 Salzburg, Austria

[2] Vienna Med Univ, Dept Gastroenterol & Hepatol, A-1090 Vienna, Austria

[3] Vienna Med Univ, Dept Clin Pathol, A-1090 Vienna, Austria

[4] St Anna Childrens Hosp, A-1090 Vienna, Austria

关键词: Computer-assisted pit-pattern classification;    Wavelet transformation;    Colorectal cancer;    Color-texture analysis;   

DOI  :  10.1016/j.patcog.2008.07.012

来源: Elsevier

【 摘 要 】

In this paper, we show that zoom-endoscopy images can be well classified according to the pit-pattern classification scheme by using texture-analysis methods in different wavelet domains. We base our approach on three different variants of the wavelet transform and propose that the color channels of the RGB and LAB color model are an important source for computing image features with high discriminative power. Color-channel information is incorporated by either using simple feature vector concatenation and cross-cooccurrence matrices in the wavelet domain. Our experimental results based on k-nearest neighbor classification and forward feature selection exemplify the advantages of the different wavelet transforms and show that color-image analysis is superior to grayscale-image analysis regarding our medical image classification problem. (C) 2008 Elsevier Ltd. All rights reserved.

【 授权许可】

Free