AIMC Topic: Diffusion Tensor Imaging

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Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework.

Scientific reports Jan 17, 2022
Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease and cognitive impairment at 1 year follow-up. Typical grading of EPVS is often challenging and time...
Retrospective Studies Female Male Deep Learning Humans Image Interpretation, Computer-Assisted Neuroimaging Diffusion Tensor Imaging Glymphatic System Imaging, Three-Dimensional Stroke Patient Acuity
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Effects of a Brain-Computer Interface-Operated Lower Limb Rehabilitation Robot on Motor Function Recovery in Patients with Stroke.

Journal of healthcare engineering Dec 20, 2021
PURPOSE: To observe the effect of a brain-computer interface-operated lower limb rehabilitation robot (BCI-LLRR) on functional recovery from stroke and to explore mechanisms.
Brain-Computer Interfaces Robotics Humans Stroke Rehabilitation Diffusion Tensor Imaging Lower Extremity Stroke Upper Extremity Recovery of Function Activities of Daily Living
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Can we predict anti-seizure medication response in focal epilepsy using machine learning?

Clinical neurology and neurosurgery Nov 16, 2021
OBJECTIVE: The aim of this study was to evaluate the feasibility of machine learning approach based on clinical factors and diffusion tensor imaging (DTI) to predict anti-seizure medication (ASM) response in focal epilepsy. We hypothesized that ASM r...
Diffusion Tensor Imaging Epilepsies, Partial Adult Male Retrospective Studies Humans Middle Aged Predictive Value of Tests ROC Curve Female Machine Learning Treatment Outcome Anticonvulsants Young Adult
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Skilled reach training enhances robotic gait training to restore overground locomotion following spinal cord injury in rats.

Behavioural brain research Aug 3, 2021
Rehabilitative training has been shown to improve motor function following spinal cord injury (SCI). Unfortunately, these gains are primarily task specific; where reach training only improves reaching, step training only improves stepping and stand t...
Humans Animals Rats Spinal Cord Injuries Diffusion Tensor Imaging Motor Activity Gait Disorders, Neurologic Disease Models, Animal Robotics Behavior, Animal Neurological Rehabilitation
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Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Human brain mapping Jul 29, 2021
Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level...
Schizophrenia Humans White Matter Machine Learning Diffusion Tensor Imaging Male Precision Medicine Middle Aged Female Models, Theoretical Predictive Value of Tests Young Adult Adult
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SuperDTI: Ultrafast DTI and fiber tractography with deep learning.

Magnetic resonance in medicine Jul 26, 2021
PURPOSE: To develop a deep learning-based reconstruction framework for ultrafast and robust diffusion tensor imaging and fiber tractography.
White Matter Diffusion Tensor Imaging Anisotropy Diffusion Magnetic Resonance Imaging Humans Deep Learning Image Processing, Computer-Assisted
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Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration-A machine learning approach.

PloS one Jul 22, 2021
Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) is a newly developed technique that combines MR-based measurements of magnetic flux density with diffusion tensor MRI (DT-MRI) data to reconstruct electrical conductivity ...
Electric Conductivity Phantoms, Imaging Diffusion Tensor Imaging Machine Learning Electromagnetic Fields Humans Algorithms
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Interpretable deep learning as a means for decrypting disease signature in multiple sclerosis.

Journal of neural engineering Jul 19, 2021
The mechanisms driving multiple sclerosis (MS) are still largely unknown, calling for new methods allowing to detect and characterize tissue degeneration since the early stages of the disease. Our aim is to decrypt the microstructural signatures of t...
Multiple Sclerosis, Relapsing-Remitting Magnetic Resonance Imaging Multiple Sclerosis Diffusion Tensor Imaging Humans Deep Learning
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Deep sr-DDL: Deep structurally regularized dynamic dictionary learning to integrate multimodal and dynamic functional connectomics data for multidimensional clinical characterizations.

NeuroImage Jul 14, 2021
We propose a novel integrated framework that jointly models complementary information from resting-state functional MRI (rs-fMRI) connectivity and diffusion tensor imaging (DTI) tractography to extract biomarkers of brain connectivity predictive of b...
Neural Networks, Computer Magnetic Resonance Imaging Databases, Factual Multimodal Imaging Autism Spectrum Disorder Humans Connectome Diffusion Tensor Imaging Deep Learning Image Processing, Computer-Assisted
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Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth.

Human brain mapping Jul 9, 2021
Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or ...
White Matter Nerve Net Diffusion Tensor Imaging Human Development Behavioral Symptoms Models, Theoretical Age Factors Gray Matter Adolescent Child, Preschool Child Humans Machine Learning Male Female Young Adult Psychometrics Adult
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