The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations
Year: 2009
Type: article
Abstract: The objective of this study was to develop anatomically correct whole body human models of an adult male (34 years old), an adult female (26 years old) and two children (an 11-year-old girl and a six-year-old boy) for the optimized evaluation of electromagnetic exposure. These four models are referred to as the Virtual Family. They are based on high resolution magnetic resonance (MR) images of healthy volunteers. More than 80 different tissue types were distinguished during the segmentation. To improve the accuracy and the effectiveness of the segmentation, a novel semi-automated tool was used to analyze and segment the data. All tissues and organs were reconstructed as three-dimensional (3D) unstructured triangulated surface objects, yielding high precision images of individual features of the body. This greatly enhances the meshing flexibility and the accuracy with respect to thin tissue layers and small organs in comparison with the traditional voxel-based representation of anatomical models. Conformal computational techniques were also applied. The techniques and tools developed in this study can be used to more effectively develop future models and further improve the accuracy of the models for various applications. For research purposes, the four models are provided for free to the scientific community.
Source: Physics in Medicine and Biology
Authors: Andreas Christ, Wolfgang Kainz, Eckhart G Hahn, Katharina Honegger, Marcel Zefferer, Esra Neufeld, Wolfgang Rascher, Rolf Janka, Werner Bautz, Ji Chen, Berthold Kiefer, Peter Schmitt, Hans-Peter Hollenbach, Jianxiang Shen, Michael Oberle, Dominik Szczerba, Anthony Kam, Joshua W Guag, Niels Kuster
Institutions: Foundation for Research on Information Technologies in Society, United States Food and Drug Administration, Center for Devices and Radiological Health, Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsklinikum Erlangen, ETH Zurich, University of Houston, Siemens Healthineers (Germany), Johns Hopkins University, Johns Hopkins Bayview Medical Center
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W2140796340