{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Paris G"],"funding":["Narodowa Agencja Wymiany Akademickiej","Ministerio de Ciencia e Innovación"],"pagination":["440-453"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9826470"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["89(1)"],"pubmed_abstract":["<h4>Purpose</h4>We seek to reformulate the so-called Propagator Anisotropy (PA) and Non-Gaussianity (NG), originally conceived for the Mean Apparent Propagator diffusion MRI (MAP-MRI), to the Micro-Structure adaptive convolution kernels and dual Fourier Integral Transforms (MiSFIT). These measures describe relevant normalized features of the Ensemble Average Propagator (EAP).<h4>Theory and methods</h4>First, the indices, which are defined as the EAP's dissimilarity from an isotropic (PA) or a Gaussian (NG) one, are analytically reformulated within the MiSFIT framework. Then a comparison between the resulting maps is drawn by means of a visual analysis, a quantitative assessment via numerical simulations, a test-retest study across the MICRA dataset (6 subjects scanned five times) and, fina"],"journal":["Magnetic resonance in medicine"],"pubmed_title":["Efficient estimation of propagator anisotropy and non-Gaussianity in multishell diffusion MRI with micro-structure adaptive convolution kernels and dual Fourier integral transforms."],"pmcid":["PMC9826470"],"funding_grant_id":["RTI2018‐094569‐B‐I00","PPN/BEK/2019/1/00421","PID2021‐124407NB‐I00"],"pubmed_authors":["Paris G","Aja-Fernandez S","Pieciak T","Tristan-Vega A"],"additional_accession":[]},"is_claimable":false,"name":"Efficient estimation of propagator anisotropy and non-Gaussianity in multishell diffusion MRI with micro-structure adaptive convolution kernels and dual Fourier integral transforms.","description":"<h4>Purpose</h4>We seek to reformulate the so-called Propagator Anisotropy (PA) and Non-Gaussianity (NG), originally conceived for the Mean Apparent Propagator diffusion MRI (MAP-MRI), to the Micro-Structure adaptive convolution kernels and dual Fourier Integral Transforms (MiSFIT). These measures describe relevant normalized features of the Ensemble Average Propagator (EAP).<h4>Theory and methods</h4>First, the indices, which are defined as the EAP's dissimilarity from an isotropic (PA) or a Gaussian (NG) one, are analytically reformulated within the MiSFIT framework. Then a comparison between the resulting maps is drawn by means of a visual analysis, a quantitative assessment via numerical simulations, a test-retest study across the MICRA dataset (6 subjects scanned five times) and, fina","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan","modification":"2025-04-05T10:27:29.091Z","creation":"2025-04-05T10:27:29.091Z"},"accession":"S-EPMC9826470","cross_references":{"pubmed":["36121312"],"doi":["10.1002/mrm.29435"]}}