Zobrazeno 1 - 10
of 30
pro vyhledávání: '"M. Okan Irfanoglu"'
Autor:
Chantal M.W. Tax, Matteo Bastiani, Jelle Veraart, Eleftherios Garyfallidis, M. Okan Irfanoglu
Publikováno v:
NeuroImage, Vol 249, Iss , Pp 118830- (2022)
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropr
Externí odkaz:
https://doaj.org/article/83add749594545eea568c3968750d097
Publikováno v:
Magnetic Resonance in Medicine
Purpose To use diffusion measurements to map the spatial dependence of the magnetic field produced by the gradient coils of an MRI scanner with sufficient accuracy to correct errors in quantitative diffusion MRI (DMRI) caused by gradient nonlinearity
Autor:
Chantal M.W. Tax, Matteo Bastiani, Jelle Veraart, Eleftherios Garyfallidis, M. Okan Irfanoglu
Publikováno v:
NeuroImage, Vol 249, Iss, Pp 118830-(2022)
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropr
Publikováno v:
Magnetic Resonance in Medicine
PURPOSE To assess the effects of blip-up and -down echo planar imaging (EPI) acquisition designs, with different choices of phase-encoding directions (PEDs) on the reproducibility of diffusion MRI (dMRI)-derived metrics in the human brain. METHODS Di
Autor:
M. Okan Irfanoglu, Carlo Pierpaoli, Neda Sadeghi, Liv S. Clasen, Nancy Raitano Lee, Elizabeth I. Adeyemi, Catherine J. Stoodley, Amritha Nayak
Publikováno v:
Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-13 (2020)
Scientific Reports, Vol 10, Iss 1, Pp 1-13 (2020)
Quantitative magnetic resonance imaging (MRI) investigations of brain anatomy in children and young adults with Down syndrome (DS) are limited, with no diffusion tensor imaging (DTI) studies covering that age range. We used DTI-driven tensor based mo
Publikováno v:
Magnetic Resonance in Medicine
Purpose To propose a methodology for assessment of algorithms that correct distortions due to motion, eddy-currents, and echo planar imaging in diffusion weighted images (DWIs). Methods The proposed method evaluates correction performance by measurin
Autor:
Alexandru V. Avram, M. Okan Irfanoglu, Carlo Pierpaoli, Evren Özarslan, Michal E. Komlosh, Sharon L. Juliano, Alan S. Barnett, Susan C. Schwerin, C. Guan Koay, Elizabeth B. Hutchinson
Publikováno v:
Magnetic Resonance in Medicine. 78:1767-1780
Purpose This study was a systematic evaluation across different and prominent diffusion MRI models to better understand the ways in which scalar metrics are influenced by experimental factors, including experimental design (diffusion-weighted imaging
Autor:
John A. Butman, Alexandru V. Avram, M. Okan Irfanoglu, Amber Simmons, Craig Weinkauf, Peter J. Basser, Neekita Jikaria, Anita D Moses, Lawrence L. Latour, Adam Bernstein, Dzung L. Pham, Martin R Cota, L. Christine Turtzo, Neville Gai
We describe a pipeline for constructing a study-specific template of diffusion propagators measured with mean apparent propagator (MAP) MRI that supports direct voxelwise analysis of differences between propagators across multiple data sets. The pipe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b881c4a21db6dff73690b0af11edb005
https://doi.org/10.1101/697284
https://doi.org/10.1101/697284
Autor:
Neda Sadeghi, Elizabeth B. Hutchinson, Amritha Nayak, Jeffrey Jenkins, M. Okan Irfanoglu, Cibu Thomas, Carlo Pierpaoli
Publikováno v:
NeuroImage. 132:439-454
In this work, we propose DR-TAMAS (Diffeomorphic Registration for Tensor Accurate alignMent of Anatomical Structures), a novel framework for intersubject registration of Diffusion Tensor Imaging (DTI) data sets. This framework is optimized for brain
Autor:
Joelle E. Sarlls, Carlo Pierpaoli, Alexandru V. Avram, Elizabeth B. Hutchinson, M. Okan Irfanoglu, Cibu Thomas, Evren Özarslan, Peter J. Basser, Alan S. Barnett
Publikováno v:
NeuroImage. 127:422-434
Diffusion tensor imaging (DTI) is the most widely used method for characterizing noninvasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its a