AIMC Topic: White Matter
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Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia.
PloS one
Sep 15, 2022
PURPOSE: To validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular...
Deep Diffusion MRI Registration (DDMReg): A Deep Learning Method for Diffusion MRI Registration.
IEEE transactions on medical imaging
Jun 1, 2022
In this paper, we present a deep learning method, DDMReg, for accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations r...
Volumetric segmentation of white matter tracts with label embedding.
NeuroImage
Jan 26, 2022
Convolutional neural networks have achieved state-of-the-art performance for white matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with th...
Deep learning reveals disease-specific signatures of white matter pathology in tauopathies.
Acta neuropathologica communications
Oct 21, 2021
Although pathology of tauopathies is characterized by abnormal tau protein aggregation in both gray and white matter regions of the brain, neuropathological investigations have generally focused on abnormalities in the cerebral cortex because the can...
Microscale characterisation of the time-dependent mechanical behaviour of brain white matter.
Journal of the mechanical behavior of biomedical materials
Oct 19, 2021
Brain mechanics is a topic of deep interest because of the significant role of mechanical cues in both brain function and form. Specifically, capturing the heterogeneous and anisotropic behaviour of cerebral white matter (WM) is extremely challenging...
A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.
Neuroradiology
Oct 2, 2021
PURPOSE: White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the cli...
Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT.
NeuroImage
Sep 25, 2021
Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more wide...
Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter.
NeuroImage
Sep 22, 2021
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur...
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...
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.
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