Gabor textons for classification of gastroenterology images
Farhan Riaz, Miguel Areia, F. Baldaque Silva, Mário Jorge Dinis-Ribeiro, Pedro Pimentel‐Nunes, Miguel Tavares Coimbra · 2011
Automatic classification of cancer lesions for gastroenterology imaging scenarios poses novel challenges to computer assisted decision systems, owing to their distinct visual characteristics such as reduced color spaces or natural organic textures. In this paper, we explore the prospects of using Gabor filters in a texton framework for the classification of images from two distinct imaging modalities (chromoendoscopy and narrow-band imaging) into three different groups: normal, precancerous and cancerous. Results show that they produce consistent results for both imaging modalities, hinting on their possible generic use for the classification of in-body images.