AIMC Topic: Diffusion Tensor Imaging
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Assessing changes in whole-brain structural connectivity in the unilateral 6-hydroxydopamine rat model of Parkinson's disease using diffusion imaging and tractography.
Journal of neural engineering
Jul 7, 2025
Parkinson's disease (PD) is a multifactorial, progressive neurodegenerative disease that has a profound impact on those it afflicts. Its hallmark pathophysiology is characterized by degeneration of dopaminergic (DA) neurons in the midbrain which trig...
BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network.
Neuroscience
Jun 19, 2025
Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work p...
Aphasia severity prediction using a multi-modal machine learning approach.
NeuroImage
Jun 17, 2025
The present study examined an integrated multiple neuroimaging modality (T1 structural, Diffusion Tensor Imaging (DTI), and resting-state FMRI (rsFMRI)) to predict aphasia severity using Western Aphasia Battery-Revised Aphasia Quotient (WAB-R AQ) in ...
Associations among white matter microstructural changes and the development of emotional reactivity and regulation in infancy.
Molecular psychiatry
Apr 23, 2025
Deficits in emotional reactivity and regulation assessed in infancy, including high levels of negative emotionality (NE), low positive emotionality (PE) and low soothability, can predict future affective and behavioral disorders. White matter (WM) tr...
Uncertainty mapping and probabilistic tractography using Simulation-based Inference in diffusion MRI: A comparison with classical Bayes.
Medical image analysis
Apr 20, 2025
Simulation-Based Inference (SBI) has recently emerged as a powerful framework for Bayesian inference: Neural networks are trained on simulations from a forward model, and learn to rapidly estimate posterior distributions. We here present an SBI frame...
A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease.
Scientific reports
Apr 16, 2025
The heterogeneity of cerebral small vessel disease (CSVD) with mild cognitive impairment (MCI) presents a challenge for diagnosis and classification. This study aims to propose a multimodal magnetic resonance imaging (MRI)-based machine learning fram...
Accelerated diffusion tensor imaging with self-supervision and fine-tuning.
Scientific reports
Apr 14, 2025
Diffusion tensor imaging (DTI) is essential for assessing brain microstructure but requires long acquisition times, limiting clinical use. Recent deep learning (DL) approaches, such as SuperDTI or deepDTI, improve DTI metrics but demand large, high-q...
Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks.
Medical image analysis
Apr 9, 2025
Multimodal neuroimaging data modeling has become a widely used approach but confronts considerable challenges due to their heterogeneity, which encompasses variability in data types, scales, and formats across modalities. This variability necessitate...
Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning.
Scientific reports
Feb 24, 2025
Diffusion magnetic resonance imaging (diffusion MRI) is widely employed to probe the diffusive motion of water molecules within the tissue. Numerous diseases and processes affecting the central nervous system can be detected and monitored via diffusi...
Coupling analysis of diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) with abnormal cerebral blood flow in methamphetamine-dependent patients and its application in machine-learning-based classification.
Journal of affective disorders
Feb 15, 2025
BACKGROUND: Diffusion tensor imaging (DTI) analysis along the perivascular space (ALPS) index is currently widely employed to evaluate the neurophysiological activity in various neuropsychiatric disorders. However, there remains a scarcity of studies...
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