AIMC Topic: Brain

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An Efficient Approach for Detection of Various Epileptic Waves Having Diverse Forms in Long Term EEG Based on Deep Learning.

Brain topography Mar 4, 2025
EEG is the most powerful tool for epilepsy discharge detection in brain. Visual evaluation is hard in long term monitoring EEG data as huge amount of data needs to be inspected. Considering the fast and efficient results from deep learning networks e...
Epilepsy Signal Processing, Computer-Assisted Neural Networks, Computer Brain Female Deep Learning Electroencephalography Adult Male Humans
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Deep learning based image enhancement for dynamic non-Cartesian MRI: Application to "silent" fMRI.

Computers in biology and medicine Mar 3, 2025
Radial based non-Cartesian sequences may be used for silent functional MRI examinations particularly in settings where scanner noise could pose issues. However, to achieve reasonable temporal resolution, under-sampled 3D radial k-space commonly resul...
Humans Brain Image Enhancement Deep Learning Connectome Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.

Neural networks : the official journal of the International Neural Network Society Feb 28, 2025
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...
Machine Learning Mental Disorders Brain Humans Female Brain Mapping Depressive Disorder, Major Rest Adult Magnetic Resonance Imaging Male
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A hybrid network based on multi-scale convolutional neural network and bidirectional gated recurrent unit for EEG denoising.

Neuroscience Feb 28, 2025
Electroencephalogram (EEG) signals are time series data containing abundant brain information. However, EEG frequently contains various artifacts, such as electromyographic, electrooculographic, and electrocardiographic. These artifacts can change EE...
Signal Processing, Computer-Assisted Humans Deep Learning Neural Networks, Computer Artifacts Brain Signal-To-Noise Ratio Convolutional Neural Networks Electroencephalography
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Minimal Neural Network Conditions for Encoding Future Interactions.

International journal of neural systems Feb 28, 2025
Space and time are fundamental attributes of the external world. Deciphering the brain mechanisms involved in processing the surrounding environment is one of the main challenges in neuroscience. This is particularly defiant when situations change ra...
Brain Learning Models, Neurological Decision Making Time Perception Humans Neural Networks, Computer
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Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.

Sensors (Basel, Switzerland) Feb 28, 2025
BACKGROUND: Infant brain tissue segmentation from MRI data is a critical task in medical imaging, particularly challenging due to the evolving nature of tissue contrasts in the early months of life. The difficulty increases as gray matter (GM) and wh...
Imaging, Three-Dimensional Spatio-Temporal Analysis Humans Cerebrospinal Fluid Image Processing, Computer-Assisted Deep Learning Datasets as Topic Brain Magnetic Resonance Imaging Gray Matter Convolutional Neural Networks Infant White Matter
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AutoDPS: An unsupervised diffusion model based method for multiple degradation removal in MRI.

Computer methods and programs in biomedicine Feb 27, 2025
BACKGROUND AND OBJECTIVE: Diffusion models have demonstrated their ability in image generation and solving inverse problems like restoration. Unlike most existing deep-learning based image restoration techniques which rely on unpaired or paired data ...
Artifacts Magnetic Resonance Imaging Unsupervised Machine Learning Motion Humans Algorithms Brain Image Processing, Computer-Assisted
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Improving ALS detection and cognitive impairment stratification with attention-enhanced deep learning models.

Scientific reports Feb 27, 2025
Amyotrophic lateral sclerosis (ALS) is a fatal neurological disease marked by motor deterioration and cognitive decline. Early diagnosis is challenging due to the complexity of sporadic ALS and the lack of a defined risk population. In this study, we...
Humans Neural Networks, Computer Cognitive Dysfunction Male Neuroimaging Amyotrophic Lateral Sclerosis Middle Aged Attention Brain Frontotemporal Dementia Deep Learning Early Diagnosis Female Aged
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Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Translational psychiatry Feb 27, 2025
Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be a...
Adult Male Middle Aged Schizophrenia Deep Learning Magnetic Resonance Imaging Aged Aged, 80 and over Young Adult Brain Precision Medicine Female Humans
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.

BMC geriatrics Feb 26, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...
Aged Aged, 80 and over Male Algorithms Brain Female Multimodal Imaging Alzheimer Disease Disease Progression Deep Learning Magnetic Resonance Imaging Humans
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