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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...
Automatic classification of cancer lesions in tissues observed using gastroenterology imaging is a non-trivial pattern recognition task involving filtering, segmentation, feature extraction and classification. In this paper we measure the impact of a variety of segmentation algorithms (mean shift, normalized cuts, level-sets) on the automatic classification performance of gastric tissue into three...
In-body imaging technologies such as vital-stained magnification endoscopy pose novel image processing challenges to computer-assisted decision systems given their unique visual characteristics such as reduced color spaces and natural textures. In this paper we will show the potential of using adapted color features combined with local binary patterns, a texture descriptor that has exhibited good...
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