Contraction detection in small bowel from an image sequence of wireless capsule endoscopy

Authors:
Hai Vu;Tomio Echigo;Ryusuke Sagawa;Keiko Yagi;Masatsugu Shiba;Kazuhide Higuchi;Tetsuo Arakawa;Yasushi Yagi
Affiliations:
The Institute of Scientific and Industrial Research, Osaka University;Osaka Electro-Communication University;The Institute of Scientific and Industrial Research, Osaka University;Kobe Pharmaceutical University;Graduate School of Medicine, Osaka City University;Graduate School of Medicine, Osaka City University;Graduate School of Medicine, Osaka City University;The Institute of Scientific and Industrial Research, Osaka University
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Year:
2007

Citing 5
Cited 3

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Linear radial patterns characterization for automatic detection of tonic intestinal contractions

CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Identification of intestinal motility events of capsule endoscopy video analysis

ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Anisotropic feature extraction from endoluminal images for detection of intestinal contractions

MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II

Detection of contractions in adaptive transit time of the small bowel from wireless capsule endoscopy videos

Computers in Biology and Medicine
Towards an Interpretation of Intestinal Motility Using Capsule Endoscopy Image Sequences

PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Analysis of Crohn's disease lesions in capsule endoscopy images

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a method for automatic detection of contractions in the small bowel through analyzing Wireless Capsule Endoscopic images. Based on the characteristics of contraction images, a coherent procedure that includes analyzes of the temporal and spatial features is proposed. For temporal features, the image sequence is examined to detect candidate contractions through the changing number of edges and an evaluation of similarities between the frames of each possible contraction to eliminate cases of low probability. For spatial features, descriptions of the directions at the edge pixels are used to determine contractions utilizing a classification method. The experimental results show the effectiveness of our method that can detect a total of 83% of cases. Thus, this is a feasible method for developing tools to assist in diagnostic procedures in the small bowel.