AIMC Topic: Brain
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Brain multi modality image inpainting via deep learning based edge region generative adversarial network.
Technology and health care : official journal of the European Society for Engineering and Medicine
Dec 25, 2024
A brain tumor (BT) is considered one of the most crucial and deadly diseases in the world, as it affects the central nervous system and its main functions. Headaches, nausea, and balance problems are caused by tumors pressing on nearby brain tissue a...
Diagnosis of major depressive disorder using a novel interpretable GCN model based on resting state fMRI.
Neuroscience
Dec 25, 2024
The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such as dataset limitations and clinical variability. Resting-state functional magnetic resonance imaging (Rs-fMRI) can reflect the fluctuation data of br...
Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.
Neural networks : the official journal of the International Neural Network Society
Dec 24, 2024
Neuroimaging techniques including functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) have shown promise in detecting functional abnormalities in various brain disorders. However, existing studies often focus on a single domai...
Detection and location of EEG events using deep learning visual inspection.
PloS one
Dec 23, 2024
The electroencephalogram (EEG) is a major diagnostic tool that provides detailed insight into the electrical activity of the brain. This signal contains a number of distinctive waveform patterns that reflect the subject's health state in relation to ...
Decoding thoughts, encoding ethics: A narrative review of the BCI-AI revolution.
Brain research
Dec 22, 2024
OBJECTIVES: This narrative review aims to analyze mechanisms underlying Brain-Computer Interface (BCI) and Artificial Intelligence (AI) integration, evaluate recent advances in signal acquisition and processing techniques, and assess AI-enhanced neur...
Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph convolutional networks.
Neural networks : the official journal of the International Neural Network Society
Dec 20, 2024
Correctly diagnosing Alzheimer's disease (AD) and identifying pathogenic brain regions and genes play a vital role in understanding the AD and developing effective prevention and treatment strategies. Recent works combine imaging and genetic data, an...
Improved deep learning-based IVIM parameter estimation via the use of more "realistic" simulated brain data.
Medical physics
Dec 20, 2024
BACKGROUND: Due to the low signal-to-noise ratio (SNR) and the limited number of b-values, precise parameter estimation of intravoxel incoherent motion (IVIM) imaging remains an open issue to date, especially for brain imaging where the relatively sm...
Classifying Alzheimer's Disease Using a Finite Basis Physics Neural Network.
Microscopy research and technique
Dec 20, 2024
The disease amyloid plaques, neurofibrillary tangles, synaptic dysfunction, and neuronal death gradually accumulate throughout Alzheimer's disease (AD), resulting in cognitive decline and functional disability. The challenges of dataset quality, inte...
Machine Learning Recognizes Stages of Parkinson's Disease Using Magnetic Resonance Imaging.
Sensors (Basel, Switzerland)
Dec 20, 2024
Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD) and Parkinson's disease (PD), are debilitating conditions that affect millions worldwide, and the number of cases is expected to rise significantly in the coming years. Because early ...
Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies.
Sensors (Basel, Switzerland)
Dec 20, 2024
Monitoring cerebral oxygenation and metabolism, using a combination of invasive and non-invasive sensors, is vital due to frequent disruptions in hemodynamic regulation across various diseases. These sensors generate continuous high-frequency data st...
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