#diffusionmri — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #diffusionmri, aggregated by home.social.
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Is it just me, or are #MRI people really bad at keeping the difference between afferent and efferent connections straight? There's a whole lot of papers that seem to just assume that if they do #DiffusionTensorImaging, and pick a seed region, that all of the streamlines they get correspond to efferents from that site. And if they cite another paper as evidence, it's often another #DiffusionMRI paper that just asserts the same thing without obvious reference to anatomical ground truth.
If you don't reference an actual #Neuroanatomy paper that worked out which direction(s) your fibers are projecting, you can't claim anything about whether your seed projects to, from, or merely passes through any other ROI along your streamlines! I think a lot of times the answer is indeed known, but cite some real anatomy papers so your readers can tell. This problem isn't universal, but it does seem weirdly common.
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Is it just me, or are #MRI people really bad at keeping the difference between afferent and efferent connections straight? There's a whole lot of papers that seem to just assume that if they do #DiffusionTensorImaging, and pick a seed region, that all of the streamlines they get correspond to efferents from that site. And if they cite another paper as evidence, it's often another #DiffusionMRI paper that just asserts the same thing without obvious reference to anatomical ground truth.
If you don't reference an actual #Neuroanatomy paper that worked out which direction(s) your fibers are projecting, you can't claim anything about whether your seed projects to, from, or merely passes through any other ROI along your streamlines! I think a lot of times the answer is indeed known, but cite some real anatomy papers so your readers can tell. This problem isn't universal, but it does seem weirdly common.
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Is it just me, or are #MRI people really bad at keeping the difference between afferent and efferent connections straight? There's a whole lot of papers that seem to just assume that if they do #DiffusionTensorImaging, and pick a seed region, that all of the streamlines they get correspond to efferents from that site. And if they cite another paper as evidence, it's often another #DiffusionMRI paper that just asserts the same thing without obvious reference to anatomical ground truth.
If you don't reference an actual #Neuroanatomy paper that worked out which direction(s) your fibers are projecting, you can't claim anything about whether your seed projects to, from, or merely passes through any other ROI along your streamlines! I think a lot of times the answer is indeed known, but cite some real anatomy papers so your readers can tell. This problem isn't universal, but it does seem weirdly common.
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Scientists have found a new way to map the insular cortex, a part of the human brain that is involved in mind-body interactions. They used a technique called diffusion MRI to trace the connections between different regions of the insular cortex and other brain areas. This could help us understand how the brain integrates sensory, emotional, and cognitive information.
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Scientists have found a new way to map the insular cortex, a part of the human brain that is involved in mind-body interactions. They used a technique called diffusion MRI to trace the connections between different regions of the insular cortex and other brain areas. This could help us understand how the brain integrates sensory, emotional, and cognitive information.
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Scientists have found a new way to map the insular cortex, a part of the human brain that is involved in mind-body interactions. They used a technique called diffusion MRI to trace the connections between different regions of the insular cortex and other brain areas. This could help us understand how the brain integrates sensory, emotional, and cognitive information.
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Scientists have found a new way to map the insular cortex, a part of the human brain that is involved in mind-body interactions. They used a technique called diffusion MRI to trace the connections between different regions of the insular cortex and other brain areas. This could help us understand how the brain integrates sensory, emotional, and cognitive information.
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Scientists have found a new way to map the insular cortex, a part of the human brain that is involved in mind-body interactions. They used a technique called diffusion MRI to trace the connections between different regions of the insular cortex and other brain areas. This could help us understand how the brain integrates sensory, emotional, and cognitive information.
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Making smart use of PDEs beats plain GZIP for lossless compression of #DiffusionMRI data by more than 30%.
Work by Ikram Jumakulyyev, recently published in JMIV.
OA paper: https://link.springer.com/article/10.1007/s10851-023-01144-z -
Making smart use of PDEs beats plain GZIP for lossless compression of #DiffusionMRI data by more than 30%.
Work by Ikram Jumakulyyev, recently published in JMIV.
OA paper: https://link.springer.com/article/10.1007/s10851-023-01144-z -
Making smart use of PDEs beats plain GZIP for lossless compression of #DiffusionMRI data by more than 30%.
Work by Ikram Jumakulyyev, recently published in JMIV.
OA paper: https://link.springer.com/article/10.1007/s10851-023-01144-z -
Making smart use of PDEs beats plain GZIP for lossless compression of #DiffusionMRI data by more than 30%.
Work by Ikram Jumakulyyev, recently published in JMIV.
OA paper: https://link.springer.com/article/10.1007/s10851-023-01144-z -
Making smart use of PDEs beats plain GZIP for lossless compression of #DiffusionMRI data by more than 30%.
Work by Ikram Jumakulyyev, recently published in JMIV.
OA paper: https://link.springer.com/article/10.1007/s10851-023-01144-z -
Many have used bootstrapping for probabilistic tractography, but have you ever considered computing a bootstrap consensus to reduce uncertainty in #diffusionMRI? Our OA journal paper on this is now out http://doi.org/10.1111/cgf.14724 extending last year's VCBM paper on fiber tracking with model averaging.
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Many have used bootstrapping for probabilistic tractography, but have you ever considered computing a bootstrap consensus to reduce uncertainty in #diffusionMRI? Our OA journal paper on this is now out http://doi.org/10.1111/cgf.14724 extending last year's VCBM paper on fiber tracking with model averaging.
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Many have used bootstrapping for probabilistic tractography, but have you ever considered computing a bootstrap consensus to reduce uncertainty in #diffusionMRI? Our OA journal paper on this is now out http://doi.org/10.1111/cgf.14724 extending last year's VCBM paper on fiber tracking with model averaging.
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Many have used bootstrapping for probabilistic tractography, but have you ever considered computing a bootstrap consensus to reduce uncertainty in #diffusionMRI? Our OA journal paper on this is now out http://doi.org/10.1111/cgf.14724 extending last year's VCBM paper on fiber tracking with model averaging.
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FYI scientists esp #radiologists and those involved in #neurosciences
Clinica: An Open-Source Software Platform for Reproducible Clinical #Neuroscience Studies
https://www.frontiersin.org/articles/10.3389/fninf.2021.689675/full
Clinica is a set of automatic pipelines for processing and analysis of multimodal #neuroimaging data (T1-weighted #MRI, #DiffusionMRI, and #PET data) & tools for statistics, #MachineLearning, and #DeepLearining
It relies on the #BrainImaging data structure (BIDS) -
FYI scientists esp #radiologists and those involved in #neurosciences
Clinica: An Open-Source Software Platform for Reproducible Clinical #Neuroscience Studies
https://www.frontiersin.org/articles/10.3389/fninf.2021.689675/full
Clinica is a set of automatic pipelines for processing and analysis of multimodal #neuroimaging data (T1-weighted #MRI, #DiffusionMRI, and #PET data) & tools for statistics, #MachineLearning, and #DeepLearining
It relies on the #BrainImaging data structure (BIDS) -
FYI scientists esp #radiologists and those involved in #neurosciences
Clinica: An Open-Source Software Platform for Reproducible Clinical #Neuroscience Studies
https://www.frontiersin.org/articles/10.3389/fninf.2021.689675/full
Clinica is a set of automatic pipelines for processing and analysis of multimodal #neuroimaging data (T1-weighted #MRI, #DiffusionMRI, and #PET data) & tools for statistics, #MachineLearning, and #DeepLearining
It relies on the #BrainImaging data structure (BIDS) -
FYI scientists esp #radiologists and those involved in #neurosciences
Clinica: An Open-Source Software Platform for Reproducible Clinical #Neuroscience Studies
https://www.frontiersin.org/articles/10.3389/fninf.2021.689675/full
Clinica is a set of automatic pipelines for processing and analysis of multimodal #neuroimaging data (T1-weighted #MRI, #DiffusionMRI, and #PET data) & tools for statistics, #MachineLearning, and #DeepLearining
It relies on the #BrainImaging data structure (BIDS) -
FYI scientists esp #radiologists and those involved in #neurosciences
Clinica: An Open-Source Software Platform for Reproducible Clinical #Neuroscience Studies
https://www.frontiersin.org/articles/10.3389/fninf.2021.689675/full
Clinica is a set of automatic pipelines for processing and analysis of multimodal #neuroimaging data (T1-weighted #MRI, #DiffusionMRI, and #PET data) & tools for statistics, #MachineLearning, and #DeepLearining
It relies on the #BrainImaging data structure (BIDS)