Texture based classification of hyperspectral colon biopsy samples using CLBP

Authors:
Khalid Masood;Nasir Rajpoot
Affiliations:
Department of Computer Science, University of Warwick, UK;Department of Computer Science, University of Warwick, UK
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

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Abstract

Computer aided diagnosis (CAD) is aimed at supporting the pathologists in their diagnosis. In this paper, we present an algorithm for texture-based classification of colon tissue patterns. In this method, a single band is selected from its hyperspectral cube and spatial analysis is performed using circular local binary pattern (CLBP) features. A novel method for feature selection is presented resulting in the best feature set without actually running the classifier. Classification results using Gaussian kernel SVM, with an accuracy of 90%, demonstrate that texture analysis based on CLBP features is able to distinguish the benign and malignant patterns.