Paper Info
Title
Eigenmotion-based detection of intestinal contractions
Abstract
Intestinal contractions are one of the main features for analyzing intestinal motility and detecting different gastrointestinal pathologies. In this paper we propose Eigenmotion-based Contraction Detection (ECD), a novel approach for automatic annotation of intestinal contractions of video capsule endoscopy. Our approach extracts the main motion information of a set of contraction sequences in form of eigenmotions using Principal Component Analysis. Then, it uses a selection of them to represent the high dimension motion data. Finally, this contraction characterization is used to classify the contraction sequences by means of machine learning techniques. The experimental results show that motion information is useful in the contraction detection. Moreover, the proposed automatic method is essential to speed up the costly examination of the video capsule endoscopy.
Year
DOI
Venue
2007
10.1007/978-3-540-74272-2_37
CAIP
Keywords
Field
DocType
main motion information,contraction sequence,video capsule endoscopy,motion information,eigenmotion-based detection,contraction detection,automatic annotation,intestinal contraction,intestinal motility,contraction characterization,high dimension motion data,machine learning,principal component analysis
Computer vision,Contraction (grammar),Pattern recognition,Computer science,Artificial intelligence,Independent component analysis,Motion estimation,Relevance vector machine,Capsule endoscopy,Principal component analysis
Conference
Volume
ISSN
Citations 
4673
0302-9743
5
PageRank 
References 
Authors
0.51
9
5
Name
Order
Citations
PageRank
Laura Igual126618.41
Santi Seguí2859.11
Jordi Vitrià373798.14
Fernando Azpiroz4748.02
Petia Radeva51684153.53