3D Reconstruction and Visualization of Liver and Vascular Networks from CT data using VTK and IGSTK
dc.contributor.author | Oliveira, João Fradinho | en_US |
dc.contributor.author | Moyano-Cuevas, José Luis | en_US |
dc.contributor.author | Pagador, José Blas | en_US |
dc.contributor.author | Capote, Hugo | en_US |
dc.contributor.author | Sánchez-Margallo, Francisco Miguel | en_US |
dc.contributor.editor | Goncalves, Alexandrino and Fernandes, Antonio Ramires and Rodrigues, Nuno | en_US |
dc.date.accessioned | 2020-12-11T13:40:46Z | |
dc.date.available | 2020-12-11T13:40:46Z | |
dc.date.issued | 2020 | |
dc.description.abstract | Spatial reasoning of vascular structures in organs such as the liver is an imperative task performed preoperatively in resection planning when minimising risks of bleeding in a procedure and intra-operatively during surgery. Accurate automatic 3D reconstruction of surfaces from computerized tomography (CT) contours is complex or impossible without user intervention. Often the gap between scan slices is large enough to make contour correspondence between adjacent slices hard to establish and branching difficult to determine. Freely available open source libraries such as the image guided surgery toolkit and the visualization toolkit (IGSTK and VTK respectively) provide building blocks that enable one to speed up the development time whilst allowing one to focus on new algorithms that might help the user. In this paper we present a new automatic solution for visualization/spatial reasoning of vascular networks within the liver that uses two separate 3D reconstruction approaches respectively. In order to make the system automatic, instead of creating contour correspondences where often crucial data is missing between slices we create a layered approach, where the surface of the liver is represented as one or more layered closed surfaces, and vascular networks where correspondence is more complex are represented as stacks of extruded individual contour blocks. Since the geometric primitive used in either reconstruction is the triangle, other algorithms such as collision detection in resection planning can be used. | en_US |
dc.description.sectionheaders | Visão por Computador e Realidade Aumentada | |
dc.description.seriesinformation | 21o Encontro Português de Computação Gráfica | |
dc.identifier.doi | 10.2312/pt.20141322 | |
dc.identifier.isbn | 978-3-03868-130-4 | |
dc.identifier.pages | 159-166 | |
dc.identifier.uri | https://doi.org/10.2312/pt.20141322 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/pt20141322 | |
dc.publisher | The Eurographics Association | en_US |
dc.subject | 3D reconstruction | |
dc.subject | IGSTK | |
dc.subject | VTK | |
dc.subject | computerized tomography | |
dc.title | 3D Reconstruction and Visualization of Liver and Vascular Networks from CT data using VTK and IGSTK | en_US |
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