Abstract: The present invention relates to a computer-implemented method capable of automatically detecting small bowel and colonic ulcers and erosions in Crohn's capsule endoscopy image data, by classifying pixels as lesion or non-lesion, using a convolutional image feature extraction step followed by a classification step and indexing such lesions in the set of one or more classes.

Abstract: The present invention relates to a computer-implemented method capable to automatically characterize small bowel lesions in capsule endoscopy images, comprising detecting small bowel lesions in medical images by classifying pixels as lesion or non-lesion, using a convolutional image feature extraction step followed by an architecture of classification and indexing into one or more classes.

Abstract: The present invention relates to a computer-implemented method, capable of automatically detecting clinically relevant colonic pleomorphic lesions and blood or hematic traces in colon capsule endoscopy images, by classifying pixels as colonic pleomorphic lesions or blood or hematic traces, using a convolutional image feature extraction step followed by a classification and indexing step of such findings into a set of one or more classes.