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Topological Fragmentation of Medical 3D Surface Mesh Models for Multi-Hierarchy Anatomical Classification

Topological Fragmentation of Medical 3D Surface Mesh Models for Multi-Hierarchy Anatomical... Abstract High resolution 3D mesh representations of patient anatomy with appendant functional classification are of high importance in the field of clinical education and therapy planning. Thereby, classification is not always possible directly from patient morphology, thus necessitating tool support. In this work a hierarchical mesh data model for multi-hierarchy anatomical classification is introduced, allowing labeling of a patient model according to various medical taxonomies. The classification regions are thereby specified utilizing a spline representation to be placed and deformed by a medical expert at low effort. Furthermore, application of randomized dilation allows conversion of the specified regions on the surface into fragmented and closed sub-meshes, comprising the entire anatomical structure. As proof of concept, the semi-automated classification method is implemented for VTK library and visualization of the multi-hierarchy anatomical model is validated with OpenGL, successfully extracting sub-meshes of the brain lobes and preparing classification regions according to Brodmann area taxonomy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Electronics and Telecommunications de Gruyter

Topological Fragmentation of Medical 3D Surface Mesh Models for Multi-Hierarchy Anatomical Classification

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Publisher
de Gruyter
Copyright
Copyright © 2015 by the
ISSN
2300-1933
eISSN
2300-1933
DOI
10.1515/eletel-2015-0016
Publisher site
See Article on Publisher Site

Abstract

Abstract High resolution 3D mesh representations of patient anatomy with appendant functional classification are of high importance in the field of clinical education and therapy planning. Thereby, classification is not always possible directly from patient morphology, thus necessitating tool support. In this work a hierarchical mesh data model for multi-hierarchy anatomical classification is introduced, allowing labeling of a patient model according to various medical taxonomies. The classification regions are thereby specified utilizing a spline representation to be placed and deformed by a medical expert at low effort. Furthermore, application of randomized dilation allows conversion of the specified regions on the surface into fragmented and closed sub-meshes, comprising the entire anatomical structure. As proof of concept, the semi-automated classification method is implemented for VTK library and visualization of the multi-hierarchy anatomical model is validated with OpenGL, successfully extracting sub-meshes of the brain lobes and preparing classification regions according to Brodmann area taxonomy.

Journal

International Journal of Electronics and Telecommunications – de Gruyter

Published: Jun 1, 2015

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