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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Towards Automatic Polyp Detection with a Polyp Appearance Model |
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Journal Article |
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Year |
2012 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
45 |
Issue |
9 |
Pages |
3166-3182 |
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Keywords |
Colonoscopy,PolypDetection,RegionSegmentation,SA-DOVA descriptot |
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Abstract |
This work aims at the automatic polyp detection by using a model of polyp appearance in the context of the analysis of colonoscopy videos. Our method consists of three stages: region segmentation, region description and region classification. The performance of our region segmentation method guarantees that if a polyp is present in the image, it will be exclusively and totally contained in a single region. The output of the algorithm also defines which regions can be considered as non-informative. We define as our region descriptor the novel Sector Accumulation-Depth of Valleys Accumulation (SA-DOVA), which provides a necessary but not sufficient condition for the polyp presence. Finally, we classify our segmented regions according to the maximal values of the SA-DOVA descriptor. Our preliminary classification results are promising, especially when classifying those parts of the image that do not contain a polyp inside. |
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Elsevier |
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0031-3203 |
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800 |
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IbPRIA |
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Notes |
MV;SIAI |
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no |
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Call Number |
Admin @ si @ BSV2012; IAM @ iam |
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1997 |
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Author |
R. Clariso; David Masip; A. Rius |
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Title |
Student projects empowering mobile learning in higher education |
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Journal |
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Year |
2014 |
Publication |
Revista de Universidad y Sociedad del Conocimiento |
Abbreviated Journal |
RUSC |
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11 |
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Pages |
192-207 |
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1698-580X |
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OR;MV |
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Admin @ si @ CMR2014 |
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2619 |
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Author |
Jorge Bernal |
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Title |
Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps |
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Journal Article |
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Year |
2014 |
Publication |
Electronic Letters on Computer Vision and Image Analysis |
Abbreviated Journal |
ELCVIA |
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Volume |
13 |
Issue |
2 |
Pages |
9-10 |
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Keywords |
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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Author |
Victor Ponce; Mario Gorga; Xavier Baro; Petia Radeva; Sergio Escalera |
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Title |
Análisis de la expresión oral y gestual en proyectos fin de carrera vía un sistema de visión artificial |
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Journal Article |
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Year |
2011 |
Publication |
ReVisión |
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Volume |
4 |
Issue |
1 |
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La comunicación y expresión oral es una competencia de especial relevancia en el EEES. No obstante, en muchas enseñanzas superiores la puesta en práctica de esta competencia ha sido relegada principalmente a la presentación de proyectos fin de carrera. Dentro de un proyecto de innovación docente, se ha desarrollado una herramienta informática para la extracción de información objetiva para el análisis de la expresión oral y gestual de los alumnos. El objetivo es dar un “feedback” a los estudiantes que les permita mejorar la calidad de sus presentaciones. El prototipo inicial que se presenta en este trabajo permite extraer de forma automática información audiovisual y analizarla mediante técnicas de aprendizaje. El sistema ha sido aplicado a 15 proyectos fin de carrera y 15 exposiciones dentro de una asignatura de cuarto curso. Los resultados obtenidos muestran la viabilidad del sistema para sugerir factores que ayuden tanto en el éxito de la comunicación así como en los criterios de evaluación. |
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1989-1199 |
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HuPBA; MILAB;MV |
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no |
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Call Number |
Admin @ si @ PGB2011d |
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2514 |
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Author |
Mario Rojas; David Masip; A. Todorov; Jordi Vitria |
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Title |
Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models |
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Journal Article |
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Year |
2011 |
Publication |
PloS one |
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Plos |
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Volume |
6 |
Issue |
8 |
Pages |
e23323 |
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Abstract |
JCR Impact Factor 2010: 4.411
Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions |
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Public Library of Science |
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OR;MV |
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Admin @ si @ RMT2011 |
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1883 |
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