AIMC Topic: White Matter
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LST-AI: A deep learning ensemble for accurate MS lesion segmentation.
NeuroImage. Clinical
Apr 29, 2024
Automated segmentation of brain white matter lesions is crucial for both clinical assessment and scientific research in multiple sclerosis (MS). Over a decade ago, we introduced an engineered lesion segmentation tool, LST. While recent lesion segment...
Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study.
Medical image analysis
Apr 25, 2024
Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter. Fiber orientation distribution functions (FODs) are a common way of representing the orientation and density of white matter fibers. However, with s...
Enhanced Spatial Fuzzy C-Means Algorithm for Brain Tissue Segmentation in T1 Images.
Neuroinformatics
Apr 24, 2024
Magnetic Resonance Imaging (MRI) plays an important role in neurology, particularly in the precise segmentation of brain tissues. Accurate segmentation is crucial for diagnosing brain injuries and neurodegenerative conditions. We introduce an Enhance...
DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images.
Magnetic resonance imaging
Apr 15, 2024
BACKGROUND AND PURPOSE: Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR...
Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning.
Medical image analysis
Apr 6, 2024
Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and cli...
Exploring subtypes of multiple sclerosis through unsupervised machine learning of automated fiber quantification.
Japanese journal of radiology
Feb 27, 2024
PURPOSE: This study aimed to subtype multiple sclerosis (MS) patients using unsupervised machine learning on white matter (WM) fiber tracts and investigate the implications for cognitive function and disability outcomes.
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.
Medical image analysis
Feb 23, 2024
We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud repres...
White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.
Molecular psychiatry
Feb 7, 2024
White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the gener...
Deep learning-based diffusion tensor image generation model: a proof-of-concept study.
Scientific reports
Feb 5, 2024
This study created an image-to-image translation model that synthesizes diffusion tensor images (DTI) from conventional diffusion weighted images, and validated the similarities between the original and synthetic DTI. Thirty-two healthy volunteers we...
Deep learning-based white matter lesion volume on CT is associated with outcome after acute ischemic stroke.
European radiology
Jan 29, 2024
BACKGROUND: Intravenous thrombolysis (IVT) before endovascular treatment (EVT) for acute ischemic stroke might induce intracerebral hemorrhages which could negatively affect patient outcomes. Measuring white matter lesions size using deep learning (D...
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