| Records |
| Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
| Title |
Blood Vessel Characterization in Colonoscopy Images to Improve Polyp Localization |
Type |
Conference Article |
| Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
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| Volume |
1 |
Issue |
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Pages |
162-171 |
| Keywords |
Colonoscopy; Blood vessel; Linear features; Valley detection |
| Abstract |
This paper presents an approach to mitigate the contribution of blood vessels to the energy image used at different tasks of automatic colonoscopy image analysis. This goal is achieved by introducing a characterization of endoluminal scene objects which allows us to differentiate between the trace of 2-dimensional visual objects,such as vessels, and shades from 3-dimensional visual objects, such as folds. The proposed characterization is based on the influence that the object shape has in the resulting visual feature, and it leads to the development of a blood vessel attenuation algorithm. A database consisting of manually labelled masks was built in order to test the performance of our method, which shows an encouraging success in blood vessel mitigation while keeping other structures intact. Moreover, by extending our method to the only available polyp localization
algorithm tested on a public database, blood vessel mitigation proved to have a positive influence on the overall performance. |
| Address |
Barcelona; February 2013 |
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| Publisher |
SciTePress |
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800 |
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Conference |
VISIGRAPP |
| Notes |
MV; 600.054; 600.057;SIAI |
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| Call Number |
IAM @ iam @ NBS2013 |
Serial |
2198 |
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| Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
| Title |
Growing Algorithm for Intersection Detection (GRAID) in branching patterns |
Type |
Journal Article |
| Year |
2015 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVAP |
| Volume |
26 |
Issue |
2 |
Pages |
387-400 |
| Keywords |
Bifurcation ; Crossroad; Intersection ;Retina ; Vessel |
| Abstract |
Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. |
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;SIAI |
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| Call Number |
Admin @ si @MBS2015 |
Serial |
2777 |
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