Learn More
Automatic classification of lesions for gastroenterology imaging scenarios poses novel challenges to computer-assisted decision systems, which are mostly attributed to the dynamics of the image acquisition conditions. Such challenges demand that automatic systems are able to give robust characterizations of tissues irrespective of camera rotation, zoom, and(More)
BACKGROUND Three different classification systems for the evaluation of Barrett's esophagus (BE) using magnification endoscopy (ME) and narrow-band imaging (NBI) have been proposed. Until now, no comparative and external evaluation of these systems in a clinical-like situation has been performed. OBJECTIVE To compare and validate these 3 classification(More)
Gastroenterology imaging is an essential tool to detect gastrointestinal cancer in patients. Computer-assisted diagnosis is desirable to help us improve the reliability of this detection. However, traditional computer vision methodologies, mainly segmentation, do not translate well to the specific visual characteristics of a gastroenterology imaging(More)
  • 1