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
ROC curves and video analysis optimization in intestinal capsule endoscopy
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Adaptive Control of Video Display for Diagnostic Assistance by Analysis of Capsule Endoscopic Images
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Contraction detection in small bowel from an image sequence of wireless capsule endoscopy
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
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
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
MPEG-7 Visual Descriptors—Contributions for Automated Feature Extraction in Capsule Endoscopy
IEEE Transactions on Circuits and Systems for Video Technology
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Recognizing intestinal contractions from wireless capsule endoscopy (WCE) image sequences provides a non-invasive method of measurement, and suggests a solution to the problems of traditional techniques for assessing intestinal motility. Based on the characteristics of contractile patterns and information on their frequencies, the contractions can be investigated using essential image features extracted from WCE videos. In this study, we proposed a coherent three-stage procedure using temporal and spatial features. The possible contractions are recognized by changes in the edge structure of the intestinal folds in Stage 1 and evaluating similarity features in consecutive frames in Stage 2. In order to take account of the properties of contraction frequency, we consider that the possible contractions are located within windows including consecutive frames. The size of these contraction windows is adjusted according to the passage of the WCE. These procedures aim to exclude as many non-contractions as possible. True contractions are determined through spatial analysis of directional information in Stage 3. Using the proposed method, 81% of true contractions are detected with a 37% false alarm rate for evaluations in the experiments. The overall performance of this method is better than that of previous methods, in terms of both the quality and quantity indices. The results suggest feasible data for further clinical applications.