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Bifurcated Topological Optimization for IVIM
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 ar...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714828/ https://www.ncbi.nlm.nih.gov/pubmed/34975382 http://dx.doi.org/10.3389/fnins.2021.779025 |
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author | Fadnavis, Shreyas Endres, Stefan Wen, Qiuting Wu, Yu-Chien Cheng, Hu Koudoro, Serge Rane, Swati Rokem, Ariel Garyfallidis, Eleftherios |
author_facet | Fadnavis, Shreyas Endres, Stefan Wen, Qiuting Wu, Yu-Chien Cheng, Hu Koudoro, Serge Rane, Swati Rokem, Ariel Garyfallidis, Eleftherios |
author_sort | Fadnavis, Shreyas |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8714828 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87148282021-12-30 Bifurcated Topological Optimization for IVIM Fadnavis, Shreyas Endres, Stefan Wen, Qiuting Wu, Yu-Chien Cheng, Hu Koudoro, Serge Rane, Swati Rokem, Ariel Garyfallidis, Eleftherios Front Neurosci Neuroscience 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. Frontiers Media S.A. 2021-12-15 /pmc/articles/PMC8714828/ /pubmed/34975382 http://dx.doi.org/10.3389/fnins.2021.779025 Text en Copyright © 2021 Fadnavis, Endres, Wen, Wu, Cheng, Koudoro, Rane, Rokem and Garyfallidis. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Fadnavis, Shreyas Endres, Stefan Wen, Qiuting Wu, Yu-Chien Cheng, Hu Koudoro, Serge Rane, Swati Rokem, Ariel Garyfallidis, Eleftherios Bifurcated Topological Optimization for IVIM |
title | Bifurcated Topological Optimization for IVIM |
title_full | Bifurcated Topological Optimization for IVIM |
title_fullStr | Bifurcated Topological Optimization for IVIM |
title_full_unstemmed | Bifurcated Topological Optimization for IVIM |
title_short | Bifurcated Topological Optimization for IVIM |
title_sort | bifurcated topological optimization for ivim |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8714828/ https://www.ncbi.nlm.nih.gov/pubmed/34975382 http://dx.doi.org/10.3389/fnins.2021.779025 |
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