TY  - JOUR
AU  - Fernando Vilariño
AU  - Panagiota Spyridonos
AU  - Fosca De Iorio
AU  - Jordi Vitria
AU  - Fernando Azpiroz
AU  - Petia Radeva
A2  - IEEE
PY  - 2010//
TI  - Intestinal Motility Assessment With Video Capsule Endoscopy: Automatic Annotation of Phasic Intestinal Contractions
T2  - TMI
JO  - IEEE Transactions on Medical Imaging
SP  - 246
EP  - 259
VL  - 29
IS  - 2
N2  - Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions shown in a video provided by an ingestible capsule with a wireless micro-camera. The manual labeling of all the motility events requires large amount of time for offline screening in search of findings with low prevalence, which turns this procedure currently unpractical. In this paper, we propose a machine learning system to automatically detect the phasic intestinal contractions in video capsule endoscopy, driving a useful but not feasible clinical routine into a feasible clinical procedure. Our proposal is based on a sequential design which involves the analysis of textural, color, and blob features together with SVM classifiers. Our approach tackles the reduction of the imbalance rate of data and allows the inclusion of domain knowledge as new stages in the cascade. We present a detailed analysis, both in a quantitative and a qualitative way, by providing several measures of performance and the assessment study of interobserver variability. Our system performs at 70% of sensitivity for individual detection, whilst obtaining equivalent patterns to those of the experts for density of contractions.
SN  - 0278-0062
L1  - http://refbase.cvc.uab.es/files/VSI2010.pdf
UR  - http://dx.doi.org/10.1109/TMI.2009.2020753
N1  - MILAB;MV;OR;SIAI
ID  - Fernando Vilariño2010
ER  -