AJNR. American journal of neuroradiology
Nov 3, 2025
BACKGROUND AND PURPOSE: Deep learning (DL) reconstruction has been successful in realizing otherwise impracticable acceleration factors and improving image quality in conventional MRI field strengths; however, there has been limited application to ul...
Terahertz (THz) optical sensing and imaging offer significant potential in a range of biological and medical applications owing to their low-energy, non-ionizing nature, and ultra-broadband spectral information, which includes numerous molecular fing...
Synucleinopathies are a group of neurodegenerative diseases characterized by the deposition of misfolded α-synuclein (αSyn), predominantly in oligodendrocytes in multiple system atrophy (MSA) and in neurons in Lewy body diseases (LBD). The contributi...
PURPOSE: Chemical exchange saturation transfer (CEST) imaging is highly sensitive to patient motion, which can compromise the reliability of quantitative molecular analysis. This study aims to develop and validate a deep learning-based motion correct...
American journal of respiratory and critical care medicine
Nov 1, 2025
One in 10 children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood. We assessed the relationship between magnetic resonance imaging-derived upper airwa...
IEEE transactions on bio-medical engineering
Nov 1, 2025
Deep learning has significantly enhanced the research on the emerging issue of Electroencephalogram (EEG)-based visual classification and reconstruction, which has gained a growth of attention and concern recently. To promote the research progress, a...
IEEE transactions on bio-medical engineering
Nov 1, 2025
U-shaped networks and its variants have demonstrated exceptional results for medical image segmentation. In this paper, we propose a novel dual self-distillation (DSD) framework in U-shaped networks for volumetric medical image segmentation. DSD dist...
IEEE transactions on neural networks and learning systems
Nov 1, 2025
Graph convolutional networks (GCNs) have shown great prowess in learning topological relationships among electroencephalogram (EEG) channels for EEG-based emotion recognition. However, most existing GCN-only methods are designed with a single spatial...
Brain function is shaped by the coordinated activity of billions of neurons. The neurotransmitters and neuromodulators released from these neurons work together to modulate circuit function and, ultimately, behavior. Electroanalytical technologies ar...
Machine learning applications in schizophrenia neuroimaging research have undergone significant evolution since 2012. However, a comprehensive scientometric analysis of this field has not yet been conducted. This study analyzed 315 original research ...
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