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Semi-automatic colonic content analysis for diagnostic

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10.2312/eurp.20171184
 
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hdl:2117/111577

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Ceballos Inza, Víctor
Monclús Lahoya, EvaMés informacióMés informacióMés informació
Vázquez Alcocer, Pere PauMés informacióMés informacióMés informació
Bendezú García, Álvaro
Mego, Marianela
Merino, Xavier
Azpiroz Vidaur, Fernando
Navazo Álvaro, IsabelMés informacióMés informació
Document typeConference lecture
Defense date2017
PublisherEuropean Association for Computer Graphics (Eurographics)
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectGENERACION, SIMULACION Y VISUALIZACION DE MODELOS 3D A PARTIR DE GRANDES CONJUNTOS DE DATOS. APLICACIONES EN LA MEJORA DE LA CALIDAD DE VIDA DE LAS PERSONAS Y SU ENTORNO (MINECO-TIN2014-52211-C2-1-R)
Abstract
The analysis of the morphology and content of the gut is necessary in order to understand metabolic and functional gut activity and for diagnostic purposes. Magnetic resonance imaging (MRI) has become an important modality technique since it is able to visualize soft tissues using no ionizing radiation, and hence removes the need for any contrast agents. In the last few years, MRI of gastrointestinal function has advanced substantially, although scarcely any publication has been devoted to the analysis of the colon content. This paper presents a semi-automatic segmentation tool for the quantitative assessment of the unprepared colon from MRI images. This application has allowed for the analysis of the colon content in various clinical experiments. The results of the assessment have contributed to a better understanding of the functionality of the colon under different diet conditions. The last experiment carried out by medical doctors showed a marked influence of diet on colonic content, accounting for about 30% of the volume variations.
CitationCeballos, V., Monclús, E., Vázquez, P., Bendezú, Á., Mego, M., Merino, X., Azpiroz, F., Navazo, I. Semi-automatic colonic content analysis for diagnostic. A: Annual EG/VGTC Conference on Visualization. "EuroVis 2017: Eurographics/IEEE VGTC Conference on Visualization 2017: Barcelona, Spain, June 12-16, 2017: posters". Barcelona: European Association for Computer Graphics (Eurographics), 2017, p. 121-123. 
URIhttp://hdl.handle.net/2117/111577
DOI10.2312/eurp.20171184
ISBN978-3-03868-044-4
Publisher versionhttps://diglib.eg.org:443/handle/10.2312/eurp20171184
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  • Departament de Ciències de la Computació - Ponències/Comunicacions de congressos [1.235]
  • ViRVIG - Grup de Recerca en Visualització, Realitat Virtual i Interacció Gràfica - Ponències/Comunicacions de congressos [72]
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