AIMC Topic: Brain
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Longitudinal study on the impact of short-term radiological interpretation training on resting-state brain network hubs.
Trends in neuroscience and education
Apr 5, 2025
Radiological expertise develops through extensive experience in specific imaging modalities. While previous research has focused on long-term learning and neural mechanisms of expertise, the effects of short-term radiological training on resting-stat...
Comparative analysis of functional network dynamics in high and low alcohol preference mice.
Experimental neurology
Apr 4, 2025
Individual variability preference is a typical characteristic of alcohol drinking behaviors, with a higher risk for the development of alcohol use disorders (AUDs) in high alcohol preference (HP) populations. Here, we created a map of alcohol-related...
Unsupervised Domain Adaptation for Cross-Modality Cerebrovascular Segmentation.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Cerebrovascular segmentation from time-of-flight magnetic resonance angiography (TOF-MRA) and computed tomography angiography (CTA) is essential in providing supportive information for diagnosing and treatment planning of multiple intracranial vascul...
SFM-Net: Semantic Feature-Based Multi-Stage Network for Unsupervised Image Registration.
IEEE journal of biomedical and health informatics
Apr 4, 2025
It is difficult for general registration methods to establish the fine correspondence between images with complex anatomical structures. To overcome the above problem, this work presents SFM-Net, an unsupervised multi-stage semantic feature-based net...
CorrMorph: Unsupervised Deformable Brain MRI Registration Based on Correlation Mining.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Deformable image registration, as a fundamental prerequisite for many medical image analysis tasks, has received considerable attention. However, existing methods suffer from two key issues: 1) single-stream methods that stack moving and fixed images...
LGG-NeXt: A Next Generation CNN and Transformer Hybrid Model for the Diagnosis of Alzheimer's Disease Using 2D Structural MRI.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Incurable Alzheimer's disease (AD) plagues many elderly people and families. It is important to accurately diagnose and predict it at an early stage. However, the existing methods have shortcomings, such as inability to learn local and global informa...
DC-ASTGCN: EEG Emotion Recognition Based on Fusion Deep Convolutional and Adaptive Spatio-Temporal Graph Convolutional Networks.
IEEE journal of biomedical and health informatics
Apr 4, 2025
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...
An Efficient Graph Learning System for Emotion Recognition Inspired by the Cognitive Prior Graph of EEG Brain Network.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
Benefiting from the high-temporal resolution of electroencephalogram (EEG), EEG-based emotion recognition has become one of the hotspots of affective computing. For EEG-based emotion recognition systems, it is crucial to utilize state-of-the-art lear...
Robust Sensory Information Reconstruction and Classification With Augmented Spikes.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
Sensory information recognition is primarily processed through the ventral and dorsal visual pathways in the primate brain visual system, which exhibits layered feature representations bearing a strong resemblance to convolutional neural networks (CN...
Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.
IEEE transactions on neural networks and learning systems
Apr 4, 2025
The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectiv...
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