Sketch-Based Editing Tools for Tumour Segmentation in 3D Medical Images

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dc.contributor.authorHeckel, Franken_US
dc.contributor.authorMoltz, Jan H.en_US
dc.contributor.authorTietjen, Christianen_US
dc.contributor.authorHahn, Horst K.en_US
dc.contributor.editorHolly Rushmeier and Oliver Deussenen_US
dc.date.accessioned2015-02-28T16:16:24Z
dc.date.available2015-02-28T16:16:24Z
dc.date.issued2013en_US
dc.description.abstractIn the past years sophisticated automatic segmentation algorithms for various medical image segmentation problems have been developed. However, there are always cases where automatic algorithms fail to provide an acceptable segmentation. In these cases the user needs efficient segmentation editing tools, a problem which has not received much attention in research. We give a comprehensive overview on segmentation editing for three‐dimensional (3D) medical images. For segmentation editing in two‐dimensional (2D) images, we discuss a sketch‐based approach where the user modifies the segmentation in the contour domain. Based on this 2D interface, we present an image‐based as well as an image‐independent method for intuitive and efficient segmentation editing in 3D in the context of tumour segmentation in computed tomography (CT). Our editing tools have been evaluated on a database containing 1226 representative liver metastases, lung nodules and lymph nodes of different shape, size and image quality. In addition, we have performed a qualitative evaluation with radiologists and technical experts, proving the efficiency of our tools.In the past years sophisticated automatic segmentation algorithms for various medical image segmentation problems have been developed. However, there are always cases where automatic algorithms fail to provide an acceptable segmentation. In these cases the user needs efficient segmentation editing tools, a problem which has not received much attention in research. We give a comprehensive overview on segmentation editing for 3D medical images. For segmentation editing in 2D, we discuss a sketch‐based approach where the user modifies the segmentation in the contour domain. Based on this 2D interface, we present an image‐based as well as an image‐independent method for intuitive and efficient segmentation editing in 3D in the context of tumour segmentation in CT.en_US
dc.description.number8
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume32
dc.identifier.doi10.1111/cgf.12193en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12193en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectsegmentationen_US
dc.subjecteditingen_US
dc.subjectcorrectionen_US
dc.subjectinteractionen_US
dc.subjectsketchingen_US
dc.subjectcontoursen_US
dc.subject3Den_US
dc.subjectCTen_US
dc.subjectComputer Graphics [I.3.5]en_US
dc.subjectComputational Geometry and Object ModellingCurveen_US
dc.subjectsurfaceen_US
dc.subjectsoliden_US
dc.subjectand object representationsen_US
dc.subjectComputer Graphics [I.3.6]en_US
dc.subjectMethodology and TechniquesInteraction techniquesen_US
dc.subjectImage Processing and Computer Vision [I.4.6]en_US
dc.subjectSegmentationen_US
dc.titleSketch-Based Editing Tools for Tumour Segmentation in 3D Medical Imagesen_US
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