Filters








3 Hits in 2.3 sec

The Dmipy Toolbox: Diffusion MRI Multi-Compartment Modeling and Microstructure Recovery Made Easy

Rutger H. J. Fick, Demian Wassermann, Rachid Deriche
2019 Frontiers in Neuroinformatics  
Non-invasive estimation of brain microstructure features using diffusion MRI (dMRI)-known as Microstructure Imaging-has become an increasingly diverse and complicated field over the last decades.  ...  Multi-compartment (MC)-models, representing the measured diffusion signal as a linear combination of signal models of distinct tissue types, have been developed in many forms to estimate these features  ...  INTRODUCTION For over three decades, multi-compartment (MC) modeling has played a major role in driving diffusion MRI (dMRI)-based microstructure research.  ... 
doi:10.3389/fninf.2019.00064 pmid:31680924 pmcid:PMC6803556 fatcat:6kgaffmhqrdkjcj7qlz4qy7lme

Multi-Tissue Multi-Compartment models of diffusion MRI [article]

Matteo Frigo, Rutger H.J. Fick, Mauro Zucchelli, Samuel Deslauriers-Gauthier, Rachid Deriche
2021 bioRxiv   pre-print
State-of-the-art multi-compartment microstructural models of diffusion MRI (dMRI) in the human brain have limited capability to model multiple tissues at the same time.  ...  The software that allows to inspect single-TE diffusion MRI data with multi-tissue multi-compartment models is included in the publicly available Dmipy Python package.  ...  The dmipy toolbox: Diffusion mri multi-compartment modeling and microstructure recovery made easy. Frontiers in Neuroinformatics, 13(64), 2019. doi: /10.3389/ fninf2019.00064. M.  ... 
doi:10.1101/2021.01.29.428843 fatcat:azuyx5xdnzenvkgtvfcgtd4vje

Challenges for biophysical modeling of microstructure

Ileana O. Jelescu, Marco Palombo, Francesca Bagnato, Kurt G. Schilling
2020 Journal of Neuroscience Methods  
The biophysical modeling efforts in diffusion MRI have grown considerably over the past 25 years.  ...  biophysical models of diffusion.  ...  Acknowledgments The authors acknowledge support from the Center for Biomedical Imaging of the EPFL, Unil, CHUV, UniGE and HUG and the Swiss National Science Foundation grant no.  ... 
doi:10.1016/j.jneumeth.2020.108861 pmid:32692999 fatcat:bapfiafyqvcbtky3qggqibefsu