Surface Curvature Line Clustering for Polyp Detection in CT Colonography

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dc.contributor.authorZhao, Lingxiaoen_US
dc.contributor.authorRavesteijn, Vincent F. vanen_US
dc.contributor.authorBotha, Charl P.en_US
dc.contributor.authorTruyen, Roelen_US
dc.contributor.authorVos, Frans M.en_US
dc.contributor.authorPost, Frits H.en_US
dc.contributor.editorCharl Botha and Gordon Kindlmann and Wiro Niessen and Bernhard Preimen_US
dc.date.accessioned2014-01-29T17:02:08Z
dc.date.available2014-01-29T17:02:08Z
dc.date.issued2008en_US
dc.description.abstractAutomatic polyp detection is a helpful addition to laborious visual inspection in CT colonography. Traditional detection methods are based on calculating image features at discrete positions on the colon wall. However large-scale surface shapes are not captured. This paper presents a novel approach to aggregate surface shape information for automatic polyp detection. The iso-surface of the colon wall can be partitioned into geometrically homogeneous regions based on clustering of curvature lines, using a spectral clustering algorithm and a symmetric line similarity measure. Each partition corresponds with the surface area that is covered by a single cluster. For each of the clusters, a number of features are calculated, based on the volumetric shape index and the surface curvedness, to select the surface partition corresponding to the cap of a polyp. We have applied our clustering approach to nine annotated patient datasets. Results show that the surface partition-based features are highly correlated with true polyp detections and can thus be used to reduce the number of false-positive detections.en_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biomedicineen_US
dc.identifier.isbn978-3-905674-13-2en_US
dc.identifier.issn2070-5786en_US
dc.identifier.urihttps://doi.org/10.2312/VCBM/VCBM08/053-060en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.3 [Computer Graphics]: Picture/Image Generation Line and curve generationen_US
dc.titleSurface Curvature Line Clustering for Polyp Detection in CT Colonographyen_US
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VCBM 08: Eurographics Workshop on Visual Computing for Biomedicine