Integration of valley orientation distribution for polyp region identification in colonoscopy

Jorge Bernal; Javier Sánchez; Fernando Vilariño

doi:10.1007/978-3-642-28557-8_10

Integration of valley orientation distribution for polyp region identification in colonoscopy

Jorge Bernal^*, Javier Sánchez, Fernando Vilariño

^*Corresponding author for this work

Department of Computer Science

Computer Vision Center (CVC)

Research output: Chapter in Book › Chapter › Research › peer-review

4 Citations (Scopus)

Abstract

This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed description method consists of defining, for each point, a series of radial sectors around it and then accumulate the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming another approach that also integrates depth of valleys information.

Original language	English
Title of host publication	Abdominal Imaging
Subtitle of host publication	Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers
Pages	76-83
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-28557-8_10
Publication status	Published - 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7029 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Keywords

Colonoscopy
Polyp Detection
VO-DOVA descriptor

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10.1007/978-3-642-28557-8_10

Cite this

Bernal, J., Sánchez, J., & Vilariño, F. (2012). Integration of valley orientation distribution for polyp region identification in colonoscopy. In Abdominal Imaging: Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers (pp. 76-83). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7029 LNCS). https://doi.org/10.1007/978-3-642-28557-8_10

Bernal, Jorge ; Sánchez, Javier ; Vilariño, Fernando. / Integration of valley orientation distribution for polyp region identification in colonoscopy. Abdominal Imaging: Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers. 2012. pp. 76-83 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Integration of valley orientation distribution for polyp region identification in colonoscopy",

abstract = "This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed description method consists of defining, for each point, a series of radial sectors around it and then accumulate the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming another approach that also integrates depth of valleys information.",

keywords = "Colonoscopy, Polyp Detection, VO-DOVA descriptor",

author = "Jorge Bernal and Javier S{\'a}nchez and Fernando Vilari{\~n}o",

year = "2012",

doi = "10.1007/978-3-642-28557-8_10",

language = "English",

isbn = "9783642285561",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Bernal, J , Sánchez, J & Vilariño, F 2012, Integration of valley orientation distribution for polyp region identification in colonoscopy. in Abdominal Imaging: Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7029 LNCS, pp. 76-83. https://doi.org/10.1007/978-3-642-28557-8_10

Integration of valley orientation distribution for polyp region identification in colonoscopy. / Bernal, Jorge ; Sánchez, Javier ; Vilariño, Fernando.

Abdominal Imaging: Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers. 2012. p. 76-83 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7029 LNCS).

Research output: Chapter in Book › Chapter › Research › peer-review

TY - CHAP

T1 - Integration of valley orientation distribution for polyp region identification in colonoscopy

AU - Bernal, Jorge

AU - Sánchez, Javier

AU - Vilariño, Fernando

PY - 2012

Y1 - 2012

N2 - This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed description method consists of defining, for each point, a series of radial sectors around it and then accumulate the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming another approach that also integrates depth of valleys information.

AB - This work presents a region descriptor based on the integration of the information that the depth of valleys image provides. The depth of valleys image is based on the presence of intensity valleys around polyps due to the image acquisition. Our proposed description method consists of defining, for each point, a series of radial sectors around it and then accumulate the maxima of the depth of valleys image only if the orientation of the intensity valley coincides with the orientation of the sector above. We apply our descriptor to a prior segmentation of the images and we present promising results on polyp detection, outperforming another approach that also integrates depth of valleys information.

KW - Colonoscopy

KW - Polyp Detection

KW - VO-DOVA descriptor

UR - http://www.scopus.com/inward/record.url?scp=84858301134&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-28557-8_10

DO - 10.1007/978-3-642-28557-8_10

M3 - Chapter

AN - SCOPUS:84858301134

SN - 9783642285561

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 76

EP - 83

BT - Abdominal Imaging

ER -

Bernal J , Sánchez J , Vilariño F. Integration of valley orientation distribution for polyp region identification in colonoscopy. In Abdominal Imaging: Computational and Clinical Applications - Third International Workshop, Held in Conjunction with MICCAI 2011, Revised Selected Papers. 2012. p. 76-83. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-28557-8_10

Integration of valley orientation distribution for polyp region identification in colonoscopy

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