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Author |
Dan Norton; Fernando Vilariño; Onur Ferhat |
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Title |
Memory Field – Creative Engagement in Digital Collections |
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Conference Article |
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Year |
2015 |
Publication |
Internet Librarian International Conference |
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“Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields). |
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London; UK; October 2015 |
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ILI |
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MV;SIAI |
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Admin @ si @NVF2015 |
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2796 |
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Author |
Fernando Vilariño |
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Title |
Computer Vision and Performing Arts |
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Conference Article |
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Year |
2015 |
Publication |
Korean Scholars of Marketing Science |
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Seoul; Korea; October 2015 |
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KAMS |
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MV;SIAI |
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Admin @ si @Vil2015 |
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2799 |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Anisotropic Feature Extraction from Endoluminal Images for Detection of Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
9th International Conference on Medical Image Computing and Computer–Assisted Intervention |
Abbreviated Journal |
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Volume |
4191 |
Issue |
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Pages |
161–168 |
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Abstract |
Wireless endoscopy is a very recent and at the same time unique technique allowing to visualize and study the occurrence of con- tractions and to analyze the intestine motility. Feature extraction is es- sential for getting efficient patterns to detect contractions in wireless video endoscopy of small intestine. We propose a novel method based on anisotropic image filtering and efficient statistical classification of con- traction features. In particular, we apply the image gradient tensor for mining informative skeletons from the original image and a sequence of descriptors for capturing the characteristic pattern of contractions. Fea- tures extracted from the endoluminal images were evaluated in terms of their discriminatory ability in correct classifying images as either belong- ing to contractions or not. Classification was performed by means of a support vector machine classifier with a radial basis function kernel. Our classification rates gave sensitivity of the order of 90.84% and specificity of the order of 94.43% respectively. These preliminary results highlight the high efficiency of the selected descriptors and support the feasibility of the proposed method in assisting the automatic detection and analysis of contractions. |
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Copenhagen (Denmark) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
R. Larsen, M. Nielsen, and J. Sporring |
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LNCS |
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800 |
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Conference |
MICCAI06 |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ SVV2006; IAM @ iam @ SVV2006 |
Serial |
725 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Cascade analysis for intestinal contraction detection |
Type |
Conference Article |
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Year |
2006 |
Publication |
20th International Congress and exhibition Computer Assisted Radiology and Surgery |
Abbreviated Journal |
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Pages |
9-10 |
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Keywords |
intestine video analysis, anisotropic features, support vector machine, cascade of classifiers |
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Abstract |
In this work, we address the study of intestinal contractions in a novel approach based on a machine learning framework to process data from Wireless Capsule Video Endoscopy. Wireless endoscopy represents a unique way to visualize the intestine motility by creating long videos to visualize intestine dynamics. In this paper we argue that to analyze huge amount of wireless endoscopy data and define robust methods for contraction detection we should base our approach on sophisticated machine learning techniques. In particular, we propose a cascade of classifiers in order to remove different physiological phenomenon and obtain the motility pattern of small intestines. Our results show obtaining high specificity and sensitivity rates that highlight the high efficiency of the selected approach and support the feasibility of the proposed methodology in the automatic detection and analysis of intestine contractions. |
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Address |
Osaka (Japan) |
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800 |
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Conference |
CARS |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006a; IAM @ iam @ VSV2006h |
Serial |
726 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Automatic Detection of Intestinal Juices in Wireless Capsule Video Endoscopy |
Type |
Conference Article |
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Year |
2006 |
Publication |
18th International Conference on Pattern Recognition |
Abbreviated Journal |
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Volume |
4 |
Issue |
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Pages |
719-722 |
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Keywords |
Clinical diagnosis , Endoscopes , Fluids and secretions , Gabor filters , Hospitals , Image sequence analysis , Intestines , Lighting , Shape , Visualization |
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Abstract |
Wireless capsule video endoscopy is a novel and challenging clinical technique, whose major reported drawback relates to the high amount of time needed for video visualization. In this paper, we propose a method for the rejection of the parts of the video resulting not valid for analysis by means of automatic detection of intestinal juices. We applied Gabor filters for the characterization of the bubble-like shape of intestinal juices in fasting patients. Our method achieves a significant reduction in visualization time, with no relevant loss of valid frames. The proposed approach is easily extensible to other image analysis scenarios where the described pattern of bubbles can be found. |
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Address |
Hong Kong |
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ISSN |
1051-4651 |
ISBN |
0-7695-2521-0 |
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800 |
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Conference |
ICPR |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006b; IAM @ iam @ VSV2006g |
Serial |
727 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva |
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Title |
Linear Radial Patterns Characterization for Automatic Detection of Tonic Intestinal Contractions |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
Issue |
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Pages |
178–187 |
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Abstract |
This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns. |
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Address |
Cancun (Mexico) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin Heidelberg |
Editor |
.F. Mart ́ınez-Trinidad et al |
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LNCS |
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800 |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006c; IAM @ iam @ VSB2006f |
Serial |
728 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Jordi Vitria; C. Malagelada; Petia Radeva |
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Title |
A Machine Learning framework using SOMs: Applications in the Intestinal Motility Assessment |
Type |
Book Chapter |
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Year |
2006 |
Publication |
11th Iberoamerican Congress on Pattern Recognition |
Abbreviated Journal |
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Volume |
4225 |
Issue |
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Pages |
188–197 |
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Abstract |
Small Bowel Motility Assessment by means of Wireless Capsule Video Endoscopy constitutes a novel clinical methodology in which a capsule with a micro-camera attached to it is swallowed by the patient, emitting a RF signal which is recorded as a video of its trip throughout the gut. In order to overcome the main drawbacks associated with this technique -mainly related to the large amount of visualization time required-, our efforts have been focused on the development of a machine learning system, built up in sequential stages, which provides the specialists with the useful part of the video, rejecting those parts not valid for analysis. We successfully used Self Organized Maps in a general semi-supervised framework with the aim of tackling the different learning stages of our system. The analysis of the diverse types of images and the automatic detection of intestinal contractions is performed under the perspective of intestinal motility assessment in a clinical environment. |
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Address |
Cancun (Mexico) |
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Publisher |
Springer Verlag |
Place of Publication |
Berlin-Heidelberg |
Editor |
J.P. Martinez–Trinidad et al |
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LNCS |
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Area |
800 |
Expedition |
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Conference |
CIARP06 |
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Notes |
MV;OR;MILAB;SIAI |
Approved |
no |
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Call Number |
BCNPCL @ bcnpcl @ VSV2006d; IAM @ iam @ VSV2006e |
Serial |
729 |
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Author |
Panagiota Spyridonos; Fernando Vilariño; Jordi Vitria; Petia Radeva; Fernando Azpiroz; Juan Malagelada |
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Title |
Device, system and method for automatic detection of contractile activity in an image frame |
Type |
Patent |
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Year |
2011 |
Publication |
US 2011/0044515 A1 |
Abbreviated Journal |
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A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system. |
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Address |
Pearl Cohen Zedek Latzer, LLP, 1500 Broadway 12th Floor, New York (NY) 10036 (US) |
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Corporate Author |
US Patent Office |
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MV;OR;MILAB;SIAI |
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no |
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Call Number |
IAM @ iam @ SVV2011 |
Serial |
1701 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
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Title |
Method for automatic classification of in vivo images |
Type |
Patent |
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Year |
2010 |
Publication |
US 2010/0046816 |
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A method for automatically detecting a post-duodenal boundary in an image stream of the gastrointestinal (GI) tract. The image stream is sampled to obtain a reduced set of images for processing. The reduced set of images is filtered to remove non-valid frames or non-valid portions of frames, thereby generating a filtered set of valid images. A polar representation of the valid images is generated. Textural features of the polar representation are processed to detect the post-duodenal boundary of the GI tract. |
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800 |
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MV;OR;MILAB;SIAI |
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no |
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IAM @ iam @ VSR2010 |
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1702 |
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Author |
Fernando Vilariño; Panagiota Spyridonos; Petia Radeva; Jordi Vitria; Fernando Azpiroz; Juan Malagelada |
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Title |
Device, system and method for measurement and analysis of contractile activity |
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Patent |
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Year |
2009 |
Publication |
US 2009/0202117 A1 |
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A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data. |
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Pearl Cohen Zedek Latzer |
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800 |
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MV;OR;MILAB;SIAI |
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no |
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IAM @ iam @ VSR2009 |
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1704 |
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Author |
F.X. Perez; F. Javier Sanchez; Xavier Binefa; Xavier Roca; Jordi Vitria; Juan J. Villanueva |
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Title |
A mathematical morphology-based system for IC´s inspection and analysis. |
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Conference Article |
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1993 |
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Institute of Physics Conferences Series |
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135 |
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10 |
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381–384 |
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Bristol |
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Institute of Physics |
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MV;OR;ISE |
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BCNPCL @ bcnpcl @ PSB1993; IAM @ iam @ PSB1993 |
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150 |
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Author |
X. Binefa; F. Javier Sanchez; F.X. Perez; Xavier Roca; Jordi Vitria; Juan J. Villanueva |
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Title |
Using defocus in optical inspection of integrated circuits |
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Conference Article |
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1993 |
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Institute of Physics Conferences Series |
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135 |
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10 |
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389-392 |
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Bristol |
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Institute of Physics |
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MV;OR;ISE |
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BCNPCL @ bcnpcl @ BSP1993; IAM @ iam @ BSP1993 |
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151 |
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Author |
F. Javier Sanchez; Jordi Vitria |
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Title |
ViLi + : Extended Lisp for image Processing and Computer Vision. |
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Conference Article |
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1994 |
Publication |
Progress in Image Analysis and Processing III |
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World Scientific |
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S.Impedovo |
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981-02-1552-5 |
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MV;OR |
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no |
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BCNPCL @ bcnpcl @ SaV1994; IAM @ iam @ SaV1994 |
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114 |
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Author |
Fernando Vilariño; Petia Radeva |
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Title |
Patch-Optimized Discriminant Active Contours for Medical Image Segmentation. |
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Conference Article |
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Year |
2002 |
Publication |
Iberoamerican Conference on Artificial Intelligence |
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Sevilla, Espanya |
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Springer Verlag |
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IBERAMIA |
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MV;MILAB;SIAI |
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BCNPCL @ bcnpcl @ ViR2002; IAM @ iam @ VRa2003 |
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320 |
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Author |
Fernando Vilariño; Petia Radeva |
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Title |
Cardiac Segmentation with Discriminant Active Contours |
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2003 |
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211–217 |
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Dynamic tracking of heart moving is one relevant target in medical imag- ing and can be helpful for analyzing heart dynamics in the study of several cardiac diseases. For this aim, a previous segmentation problem of such structures is stated, based on certain relevant features (like edges or intensity levels, textures, etc.) Clas- sical active models have been used, but they fail when overlapping structures or not well-defined contours are present. Automatic feature learning systems may be a pow- erful tool. Discriminant active contours present optimal results in this kind of problem. They are a kind of deformable models that converge to an optimal object segmenta- tion that dynamically adapts to the object contour. The feature space is designed from a filter bank in order to guarantee the search and learning of the set of relevant fea- tures for optimal classification on each part of the object. Tracking of target evolution is obtained through the whole set of images, using information from the actual and previous stages. Feedback systems are implemented to guarantee the minimum well- separable classification set in each segmentation step. Our implementation has been proved with several series of Magnetic Resonance with improved results in segmenta- tion in comparison to previous methods. |
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Palma de Mallorca |
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IOS Press |
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CCIA |
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Notes |
MV;MILAB;SIAI |
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no |
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Call Number |
BCNPCL @ bcnpcl @ ViR2003; IAM @ iam @ VRa2003 |
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426 |
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