DocumentCode :
3462674
Title :
Aligning endoluminal scene sequences in wireless capsule endoscopy
Author :
Drozdzal, Michal ; Igual, Laura ; Vitria, Jordi ; Malagelada, Carolina ; Azpiroz, Fernando ; Radeva, Petia
Author_Institution :
Comput. Vision Center, Bellaterra, Spain
fYear :
2010
fDate :
13-18 June 2010
Firstpage :
117
Lastpage :
124
Abstract :
Intestinal motility analysis is an important examination in detection of various intestinal malfunctions. One of the big challenges of automatic motility analysis is how to compare sequence of images and extract dynamic paterns taking into account the high deformability of the intestine wall as well as the capsule motion. From clinical point of view the ability to align endoluminal scene sequences will help to find regions of similar intestinal activity and in this way will provide a valuable information on intestinal motility problems. This work, for first time, addresses the problem of aligning endoluminal sequences taking into account motion and structure of the intestine. To describe motility in the sequence, we propose different descriptors based on the Sift Flow algorithm, namely: (1) Histograms of Sift Flow Directions to describe the flow course, (2) Sift Descriptors to represent image intestine structure and (3) Sift Flow Magnitude to quantify intestine deformation. We show that the merge of all three descriptors provides robust information on sequence description in terms of motility. Moreover, we develop a novel methodology to rank the intestinal sequences based on the expert feedback about relevance of the results. The experimental results show that the selected descriptors are useful in the alignment and similarity description and the proposed method allows the analysis of the WCE.
Keywords :
biological organs; endoscopes; image sequences; medical image processing; wireless sensor networks; automatic motility analysis; capsule motion; dynamic pattern extraction; endoluminal scene sequence aligning; image intestine structure; image sequence; intestinal activity; intestinal malfunctions; intestinal motility; intestinal motility analysis; intestine deformation; intestine wall deformability; sift descriptors; sift flow algorithm; sift flow direction histograms; sift flow magnitude; wireless capsule endoscopy; Data mining; Endoscopes; Histograms; Image analysis; Image motion analysis; Image sequence analysis; Intestines; Layout; Motion analysis; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
ISSN :
2160-7508
Print_ISBN :
978-1-4244-7029-7
Type :
conf
DOI :
10.1109/CVPRW.2010.5543456
Filename :
5543456
Link To Document :
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