Bifurcated topological optimization for IVIM

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dc.contributor.author Fadnavis, Shreyas
dc.contributor.author Endres, S.C. (Stefan)
dc.contributor.author Wen, Qiuting
dc.contributor.author Wu, Yu-Chien
dc.contributor.author Cheng, Hu
dc.contributor.author Koudoro, Serge
dc.contributor.author Rane, Swati
dc.contributor.author Rokem, Ariel
dc.contributor.author Garyfallidis, Eleftherios
dc.date.accessioned 2022-08-10T05:56:02Z
dc.date.available 2022-08-10T05:56:02Z
dc.date.issued 2021-12-15
dc.description.abstract In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM) for diffusion and perfusion estimation by characterizing the objective function using simplicial homology tools. We provide a robust solution via topological optimization of this model so that the estimates are more reliable and accurate. Estimating the tissue microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem. Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model we perform the optimization using simplicial homology based global optimization to better understand the topology of objective function surface. We theoretically show how the proposed methodology can recover the model parameters more accurately and consistently by casting it in a reduced subspace given by VarPro. Additionally we demonstrate that the IVIM model parameters cannot be accurately reconstructed using conventional numerical optimization methods due to the presence of infinite solutions in subspaces. The proposed method helps uncover multiple global minima by analyzing the local geometry of the model enabling the generation of reliable estimates of model parameters. en_US
dc.description.department Chemical Engineering en_US
dc.description.librarian am2022 en_US
dc.description.sponsorship The National Institute of Biomedical Imaging And Bioengineering (NIBIB) of the National Institutes of Health (NIH); University of Washington’s Royalty Research Fund; NIH grants; the German Research Foundation (DFG) and a grant from the Alfred P. Sloan Foundation and the Gordon & Betty Moore Foundation to the University of Washington eScience Institute Data Science Environment. en_US
dc.description.uri http://www.frontiersin.org/Neuroscience en_US
dc.identifier.citation Fadnavis, S., Endres, S., Wen, Q., Wu, Y.-C., Cheng, H., Koudoro, S., Rane, S., Rokem, A. & Garyfallidis, E. (2021) Bifurcated Topological Optimization for IVIM. Frontiers in Neuroscience15:779025. DOI: 10.3389/fnins.2021.779025. en_US
dc.identifier.issn 1662-453X (online)
dc.identifier.other 10.3389/fnins.2021.779025
dc.identifier.uri https://repository.up.ac.za/handle/2263/86736
dc.language.iso en en_US
dc.publisher Frontiers Media en_US
dc.rights © 2021 Fadnavis, Endres, Wen, Wu, Cheng, Koudoro, Rane, Rokem and Garyfallidis. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). en_US
dc.subject Simplicial homology en_US
dc.subject Diffusion MRI en_US
dc.subject Global optimization en_US
dc.subject Separable non-linear least squares en_US
dc.subject Variable projection en_US
dc.subject Diffusion microstructure en_US
dc.subject Magnetic resonance imaging (MRI) en_US
dc.subject Intravoxel incoherent motion (IVIM) en_US
dc.title Bifurcated topological optimization for IVIM en_US
dc.type Article en_US


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