AIMC Topic: Brain

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The neuroconnectionist research programme.

Nature reviews. Neuroscience May 30, 2023
Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have been not only lauded as the current best models of information processing ...
Neural Networks, Computer Brain Humans
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Direct synthesis of multi-contrast brain MR images from MR multitasking spatial factors using deep learning.

Magnetic resonance in medicine May 28, 2023
PURPOSE: To develop a deep learning method to synthesize conventional contrast-weighted images in the brain from MR multitasking spatial factors.
Magnetic Resonance Imaging Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Brain
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Three levels of information processing in the brain.

Bio Systems May 26, 2023
Information, the measure of order in a complex system, is the opposite of entropy, the measure of chaos and disorder. We can distinguish several levels at which information is processed in the brain. The first one is the level of serial molecular gen...
Artificial Intelligence Brain Learning Cognition Consciousness
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Deep Learning Detection and Segmentation of Brain Arteriovenous Malformation on Magnetic Resonance Angiography.

Journal of magnetic resonance imaging : JMRI May 23, 2023
BACKGROUND: The delineation of brain arteriovenous malformations (bAVMs) is crucial for subsequent treatment planning. Manual segmentation is time-consuming and labor-intensive. Applying deep learning to automatically detect and segment bAVM might he...
Deep Learning Adolescent Adult Middle Aged Magnetic Resonance Imaging Magnetic Resonance Angiography Intracranial Arteriovenous Malformations Child Image Processing, Computer-Assisted Brain Retrospective Studies Aged Young Adult Humans
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Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Medical image analysis May 23, 2023
Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. For this reason, several machine learning-based methods have been developed for the automatic qualit...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Artifacts Brain Machine Learning Deep Learning
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Deep Learning Aided Neuroimaging and Brain Regulation.

Sensors (Basel, Switzerland) May 23, 2023
Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application and the future development trend of precision neuroscience. This review aimed to render comprehensive and informative insights into the recent progress...
Magnetic Resonance Imaging Neuroimaging Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Brain
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msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.

NeuroImage May 21, 2023
Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and the auxiliary diagnosis of neurodegenerative disease. There still exists a dipole inversion problem in QSM reconstruction. Recently, deep learning ap...
Alzheimer Disease Brain Mapping Neurodegenerative Diseases Brain Deep Learning Magnetic Resonance Imaging Parkinson Disease Image Processing, Computer-Assisted Humans Algorithms
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Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI.

Academic radiology May 19, 2023
RATIONALE AND OBJECTIVES: To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T.
Neuroimaging Diffusion Magnetic Resonance Imaging Echo-Planar Imaging Deep Learning Magnetic Resonance Imaging Humans Brain
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Identification of attention deficit hyperactivity disorder with deep learning model.

Physical and engineering sciences in medicine May 16, 2023
This article explores the detection of Attention Deficit Hyperactivity Disorder, a neurobehavioral disorder, from electroencephalography signals. Due to the unstable behavior of electroencephalography signals caused by complex neuronal activity in th...
Support Vector Machine Electroencephalography Brain Deep Learning Attention Deficit Disorder with Hyperactivity Humans
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Quantification of spatially localized MRS by a novel deep learning approach without spectral fitting.

Magnetic resonance in medicine May 15, 2023
PURPOSE: To propose a novel end-to-end deep learning model to quantify absolute metabolite concentrations from in vivo J-point resolved spectroscopy (JPRESS) without using spectral fitting.
Brain Deep Learning Magnetic Resonance Spectroscopy Humans
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