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SurfaceNets for Multi-Label Segmentations with Preservation of Sharp Boundaries

We extend 3D SurfaceNets to generate surfaces of segmented 3D medical images composed of multiple materials represented as indexed labels. Our extension generates smooth, high-quality triangle meshes suitable for rendering and tetrahedralization, preserves topology and sharp boundaries between mater...

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Detalles Bibliográficos
Autor principal: Frisken, Sarah F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9623606/
https://www.ncbi.nlm.nih.gov/pubmed/36325473
Descripción
Sumario:We extend 3D SurfaceNets to generate surfaces of segmented 3D medical images composed of multiple materials represented as indexed labels. Our extension generates smooth, high-quality triangle meshes suitable for rendering and tetrahedralization, preserves topology and sharp boundaries between materials, guarantees a user-specified accuracy, and is fast enough that users can interactively explore the trade-off between accuracy and surface smoothness. We provide open-source code in the form of an extendable C++ library with a simple API, and a Qt and OpenGL-based application that allows users to import or randomly generate multi-label volumes to experiment with surface fairing parameters. In this paper, we describe the basic SurfaceNets algorithm, our extension to handle multiple materials, our method for preserving sharp boundaries between materials, and implementation details used to achieve efficient processing.