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Jordi Vitria; M. Bressan; Petia Radeva |
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Bayesian classification of cork stoppers using class-conditional independent component analysis |
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2006 |
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IEEE Transactions on Systems, Man and Cybernetics (Part C), 36(6) |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VBR2006 |
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723 |
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Author |
Jordi Vitria; M. Bressan; Petia Radeva |
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Title |
Bayesian classification of cork stoppers using class-conditional independent component analysis |
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2007 |
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IEEE Transactions on Systems, Man and Cybernetics (Part C), 37(1): 32–38 (ISI 0,482) |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VBR2007 |
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795 |
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Author |
Jordi Vitria; Petia Radeva; X. Binefa |
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Title |
EigenHistograms: using low dimensional models of color distribution for real time object recognition |
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1999 |
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Ljubliana, Slovenia, Springer-Verlag |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VRB1999a |
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29 |
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Author |
Jorge Bernal |
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Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps |
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2014 |
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Electronic Letters on Computer Vision and Image Analysis |
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ELCVIA |
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13 |
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2 |
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9-10 |
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Colonoscopy; polyp localization; polyp segmentation; Eye-tracking |
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Colorectal cancer is the fourth most common cause of cancer death worldwide and its survival rate depends on the stage in which it is detected on hence the necessity for an early colon screening. There are several screening techniques but colonoscopy is still nowadays the gold standard, although it has some drawbacks such as the miss rate. Our contribution, in the field of intelligent systems for colonoscopy, aims at providing a polyp localization and a polyp segmentation system based on a model of appearance for polyps. To develop both methods we define a model of appearance for polyps, which describes a polyp as enclosed by intensity valleys. The novelty of our contribution resides on the fact that we include in our model aspects of the image formation and we also consider the presence of other elements from the endoluminal scene such as specular highlights and blood vessels, which have an impact on the performance of our methods. In order to develop our polyp localization method we accumulate valley information in order to generate energy maps, which are also used to guide the polyp segmentation. Our methods achieve promising results in polyp localization and segmentation. As we want to explore the usability of our methods we present a comparative analysis between physicians fixations obtained via an eye tracking device and our polyp localization method. The results show that our method is indistinguishable to novice physicians although it is far from expert physicians. |
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Alicia Fornes; Volkmar Frinken |
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MV |
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Admin @ si @ Ber2014 |
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2487 |
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Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez |
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Title |
GTCreator: a flexible annotation tool for image-based datasets |
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2019 |
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International Journal of Computer Assisted Radiology and Surgery |
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IJCAR |
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14 |
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2 |
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191–201 |
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Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation |
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Abstract Purpose: Methodology evaluation for decision support systems for health is a time consuming-task. To assess performance of polyp detection
methods in colonoscopy videos, clinicians have to deal with the annotation
of thousands of images. Current existing tools could be improved in terms of
exibility and ease of use. Methods:We introduce GTCreator, a exible annotation tool for providing image and text annotations to image-based datasets.
It keeps the main basic functionalities of other similar tools while extending
other capabilities such as allowing multiple annotators to work simultaneously
on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results: The
comparison with other similar tools shows that GTCreator allows to obtain
fast and precise annotation of image datasets, being the only one which offers
full annotation editing and browsing capabilites. Conclusions: Our proposed
annotation tool has been proven to be efficient for large image dataset annota-
tion, as well as showing potential of use in other stages of method evaluation
such as experimental setup or results analysis. |
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MV; 600.096; 600.109; 600.119; 601.305 |
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Admin @ si @ BHM2019 |
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3163 |
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