29 March 2016 FEM-based simulation of a fluorescence tomography experiment using anatomical MR images
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Abstract
A hybrid system combining fluorescence molecular tomography (FMT) and magnetic resonance imaging (MRI) is attractive for preclinical imaging as it allows fusion of molecular information derived from FMT and anatomical reference data derived from MRI. We have previously developed such a system and demonstrated its performance in biological applications. For reconstruction slab geometry with homogeneous optical parameters was assumed, which led to undesirable artifacts. In order to exploit the power of the hybrid system, the use of MRI derived anatomical information, as a constraint for FMT reconstruction, appears logical. Heterogeneity of tissues and irregular surface derived from MRI can be accounted for by generating a mesh using the finite element method (FEM), and attributing optical parameters to individual mesh points. We have established a forward simulation tool based on TOAST++ to mimic an FMT experiment. MRI images were recorded on a 9.4T MR scanner using a T1-weighted pulse sequence. The voxelized dataset was processed by iso2mesh to yield a 3D-mesh. Four steps of FMT simulation were included: 1) Assignment of optical properties, 2) Specification of boundary conditions and generation of 3) excitation and 4) emission maps. FEM-derived results were compared with those obtained using the analytical solution of Green's function and with experimental data with a single fluorescent inclusion in a silicon phantom. Once, the forward modeling method is properly validated it will be used as a central element of a reconstruction algorithm for analyzing data derived from a hybrid FMT/MRI setup.
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Wuwei Ren, Wuwei Ren, Andreas Elmer, Andreas Elmer, Mark-Aurel Augath, Mark-Aurel Augath, Markus Rudin, Markus Rudin, "FEM-based simulation of a fluorescence tomography experiment using anatomical MR images", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 978828 (29 March 2016); doi: 10.1117/12.2216454; https://doi.org/10.1117/12.2216454
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