Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images

Santi Seguí; Michal Drozdzal; Ekaterina Zaytseva; Carolina Malagelada; Fernando Azpiroz; Petia Radeva; Jordi Vitrià

doi:10.1109/JBHI.2014.2304179

Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images

Santi Seguí, Michal Drozdzal, Ekaterina Zaytseva, Carolina Malagelada, Fernando Azpiroz, Petia Radeva, Jordi Vitrià

Department of Medicine

Research output: Contribution to journal › Article › Research › peer-review

Abstract

Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper, we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state-of-the-art performance for this task.

Original language	English
Pages (from-to)	1831-8
Number of pages	8
Journal	IEEE Journal of Biomedical and Health Informatics
Volume	18
Issue number	6
DOIs	https://doi.org/10.1109/JBHI.2014.2304179
Publication status	Published - Nov 2014

Keywords

Algorithms
Capsule Endoscopy/methods
Gastrointestinal Motility/physiology
Humans
Image Processing, Computer-Assisted/methods
Intestinal Diseases/physiopathology
Reproducibility of Results

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10.1109/JBHI.2014.2304179

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title = "Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images",

abstract = "Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper, we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state-of-the-art performance for this task. ",

keywords = "Algorithms, Capsule Endoscopy/methods, Gastrointestinal Motility/physiology, Humans, Image Processing, Computer-Assisted/methods, Intestinal Diseases/physiopathology, Reproducibility of Results",

author = "Santi Segu{\'i} and Michal Drozdzal and Ekaterina Zaytseva and Carolina Malagelada and Fernando Azpiroz and Petia Radeva and Jordi Vitri{\`a}",

year = "2014",

month = nov,

doi = "10.1109/JBHI.2014.2304179",

language = "English",

volume = "18",

pages = "1831--8",

number = "6",

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TY - JOUR

T1 - Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images

AU - Seguí, Santi

AU - Drozdzal, Michal

AU - Zaytseva, Ekaterina

AU - Malagelada, Carolina

AU - Azpiroz, Fernando

AU - Radeva, Petia

AU - Vitrià, Jordi

PY - 2014/11

Y1 - 2014/11

N2 - Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper, we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state-of-the-art performance for this task.

AB - Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper, we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state-of-the-art performance for this task.

KW - Algorithms

KW - Capsule Endoscopy/methods

KW - Gastrointestinal Motility/physiology

KW - Humans

KW - Image Processing, Computer-Assisted/methods

KW - Intestinal Diseases/physiopathology

KW - Reproducibility of Results

U2 - 10.1109/JBHI.2014.2304179

DO - 10.1109/JBHI.2014.2304179

M3 - Article

C2 - 25375680

VL - 18

SP - 1831

EP - 1838

IS - 6

ER -

Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images

Abstract

Keywords

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