TY  - CHAP
AU  - Fernando Vilariño
AU  - Panagiota Spyridonos
AU  - Jordi Vitria
AU  - C. Malagelada
AU  - Petia Radeva
A2  - CIARP06
ED  - J.P. Martinez–Trinidad et al
PY  - 2006//
TI  - A Machine Learning framework using SOMs:  Applications in the Intestinal Motility Assessment
T2  - LNCS
BT  - 11th Iberoamerican Congress on Pattern Recognition
SP  - 188–197
VL  - 4225
PB  - Springer Verlag
CY  - Berlin-Heidelberg
N2  - Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment.
L1  - http://refbase.cvc.uab.es/files/VSV2006e.pdf
UR  - http://dx.doi.org/10.1007/11892755_19
N1  - MV;OR;MILAB;SIAI
ID  - Fernando Vilariño2006
ER  -