Show simple item record

dc.contributor.authorAlpers, Julianen_US
dc.contributor.authorHansen, Christianen_US
dc.contributor.authorRinge, Kristinaen_US
dc.contributor.authorRieder, Christianen_US
dc.contributor.editorStefan Bruckner and Anja Hennemuth and Bernhard Kainz and Ingrid Hotz and Dorit Merhof and Christian Riederen_US
dc.date.accessioned2017-09-06T07:12:31Z
dc.date.available2017-09-06T07:12:31Z
dc.date.issued2017
dc.identifier.isbn978-3-03868-036-9
dc.identifier.issn2070-5786
dc.identifier.urihttp://dx.doi.org/10.2312/vcbm.20171240
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20171240
dc.description.abstractImage-guided thermal ablation procedures such as microwave ablation (MWA) or radiofrequency ablation (RFA) have become clinically accepted treatment options for liver tumors. The goal of these minimally invasive procedures is the destruction of focal liver malignancies using mostly needle-shaped instruments. Computed tomography (CT) imaging may be used to navigate the applicator to the target position in order to achieve complete tumor ablation. Due to limited image quality and resolution, the treatment target and risk structures may be hardly visible in intra-interventional CT-images, hampering verification of the intended applicator position. In this work, we propose a navigation guidance method based only on CT images to support the physician with additional information to reach the target position. Therefore, planning information extracted from pre-interventional images is fused with the current intra-interventional image. The visible applicator is extracted semi-automatically from the intra-interventional image. The localization of the needle instrument is used to guide the physician by display of the pathway, projection of anatomical structures, and correction suggestions. In an evaluation, we demonstrate the potential of the proposed method to improve the clinical success rate of complex liver tumor ablations while increasing the accuracy and reducing the number of intra-interventional CT images needed.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCCS Concepts
dc.subjectHuman
dc.subjectcentered computing
dc.subjectScientific visualization
dc.subjectComputing methodologies
dc.subjectObject detection
dc.subjectApplied computing
dc.subjectHealth informatics
dc.titleCT-Based Navigation Guidance for Liver Tumor Ablationen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.description.sectionheadersApplications
dc.identifier.doi10.2312/vcbm.20171240
dc.identifier.pages83-92


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record