Semi-automatic Colonic Content Analysis for Diagnostic

dc.contributor.authorCeballos, Víctoren_US
dc.contributor.authorMonclús, Evaen_US
dc.contributor.authorVázquez, Pere-Pauen_US
dc.contributor.authorBendezú, Álvaroen_US
dc.contributor.authorMego, Marianelaen_US
dc.contributor.authorMerino, Xavieren_US
dc.contributor.authorAzpiroz, Fernandoen_US
dc.contributor.authorNavazo, Isabelen_US
dc.contributor.editorAnna Puig Puig and Tobias Isenbergen_US
dc.date.accessioned2017-06-12T05:18:05Z
dc.date.available2017-06-12T05:18:05Z
dc.date.issued2017
dc.description.abstractThe 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.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEuroVis 2017 - Posters
dc.identifier.doi10.2312/eurp.20171184
dc.identifier.isbn978-3-03868-044-4
dc.identifier.pages121-123
dc.identifier.urihttps://doi.org/10.2312/eurp.20171184
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurp20171184
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]
dc.subjectApplications
dc.titleSemi-automatic Colonic Content Analysis for Diagnosticen_US
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