PURPOSE: Focal epilepsy is a risk factor for language impairment in children. We investigated whether the current state-of-the-art deep learning network on diffusion tractography connectome can accurately predict expressive and receptive language sco...
PURPOSE: To investigate whether Parkinson's disease (PD) can be differentiated from healthy controls and to identify neural circuit disorders in PD by applying a deep learning technique to parameter-weighted and number of streamlines (NOS)-based stru...
Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and ...
Deep learning (DL) has shown great potential in medical image enhancement problems, such as super-resolution or image synthesis. However, to date, most existing approaches are based on deterministic models, neglecting the presence of different source...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Sep 18, 2020
To assess the feasibility of a denoising approach with deep learning-based reconstruction (dDLR) for fast volume simultaneous multi-slice diffusion tensor imaging of the brain, noise reduction effects and the reliability of diffusion metrics were eva...
OBJECTIVE: Medial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperativel...
Progress in neuro-psychopharmacology & biological psychiatry
Aug 18, 2020
BACKGROUND: Altered structural and functional brain networks have been extensively studied in major depressive disorder (MDD) patients. However, whether the differential connectivity patterns in the rich-club organization, assessed from structural br...
PURPOSE: To develop and evaluate machine-learning methods that reconstruct fractional anisotropy (FA) values and mean diffusivities (MD) from 3-direction diffusion MRI (dMRI) acquisitions.
The Extended Frontal Aslant Tract (exFAT) is a recently described tractography-based extension of the Frontal Aslant Tract connecting Broca's territory to both supplementary and pre-supplementary motor areas, and more anterior prefrontal regions. In ...
OBJECTIVES: We aimed to evaluate the ability of feed-forward neural networks (fNNs) to predict the neurodevelopmental outcome (NDO) of very preterm neonates (VPIs) at 12 months corrected age by using biomarkers of cerebral MR proton spectroscopy (H-M...
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