AIMC Topic: Gray Matter
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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...
Identifying gray matter alterations in Cushing's disease using machine learning: An interpretable approach.
Medical physics
Apr 1, 2024
BACKGROUND: Cushing's Disease (CD) is a rare clinical syndrome characterized by excessive secretion of adrenocorticotrophic hormone, leading to significant functional and structural brain alterations as observed in Magnetic Resonance Imaging (MRI). W...
Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.
Academic radiology
Feb 29, 2024
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...
Determination of Alzheimer's disease based on morphology and atrophy using machine learning combined with automated segmentation.
Acta radiologica (Stockholm, Sweden : 1987)
Jan 9, 2024
BACKGROUND: To evaluate the degree of cerebral atrophy for Alzheimer's disease (AD), voxel-based morphometry has been performed with magnetic resonance imaging. Detailed morphological changes in a specific tissue area having the most evidence of atro...
verified anatomically aware deep learning for real-time electric field simulation.
Journal of neural engineering
Nov 28, 2023
Transcranial magnetic stimulation (TMS) has emerged as a prominent non-invasive technique for modulating brain function and treating mental disorders. By generating a high-precision magnetically evoked electric field (E-field) using a TMS coil, it en...
An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images.
Human brain mapping
Jun 19, 2023
Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution ...
HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.
European journal of radiology
Mar 15, 2023
A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability map was developed to improve the hippocampus segmentation (called HGM-cNet) due to its significance in various neuropsychiatric disorders such as Alzh...
Attention-modulated multi-branch convolutional neural networks for neonatal brain tissue segmentation.
Computers in biology and medicine
Apr 26, 2022
Accurate measurement of brain structures is essential for the evaluation of neonatal brain growth and development. The conventional methods use manual segmentation to measure brain tissues, which is very time-consuming and inefficient. Recent deep le...
QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.
Magnetic resonance in medicine
Oct 31, 2021
PURPOSE: To improve accuracy and speed of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) -based oxygen extraction fraction (OEF) mapping using a deep neural network (QQ-NET).
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...
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