AIMC Topic: Brain

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Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie Sep 16, 2023
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...
Alzheimer Disease Neuroimaging Humans Aging Machine Learning Cognitive Dysfunction Radiomics Female Male Aged Aged, 80 and over Biomarkers Brain
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Comparison of convolutional-neural-networks-based method and LCModel on the quantification of in vivo magnetic resonance spectroscopy.

Magma (New York, N.Y.) Sep 15, 2023
BACKGROUND: Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have fo...
Aspartic Acid Male Deep Learning Young Adult Signal-To-Noise Ratio Neural Networks, Computer Brain Magnetic Resonance Spectroscopy Algorithms Adult Linear Models Female Humans
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Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.

NeuroImage Sep 15, 2023
Electromagnetic source imaging (ESI) offers unique capability of imaging brain dynamics for studying brain functions and aiding the clinical management of brain disorders. Challenges exist in ESI due to the ill-posedness of the inverse problem and th...
Brain Deep Learning Humans Electrocorticography Electroencephalography Epilepsy Magnetoencephalography Magnetic Resonance Imaging Drug Resistant Epilepsy Brain Mapping
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Decoding brain complexity: Structural-functional interplay in neural networks: Comment on "Structure and function in artificial, zebrafish and human neural networks" by Peng Ji et al.

Physics of life reviews Sep 14, 2023
Zebrafish Brain Animals Humans Neural Networks, Computer
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In-Sensor Computing Realization Using Fully CMOS-Compatible TiN/HfO-Based Neuristor Array.

ACS sensors Sep 14, 2023
With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneou...
Artificial Intelligence Brain Explosive Agents Commerce Movement
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Medical image diagnosis based on adaptive Hybrid Quantum CNN.

BMC medical imaging Sep 14, 2023
Hybrid quantum systems have shown promise in image classification by combining the strengths of both classical and quantum algorithms. These systems leverage the parallel processing power of quantum computers to perform complex computations while uti...
Neural Networks, Computer Machine Learning Humans Motion Algorithms Brain
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A robust and interpretable deep learning framework for multi-modal registration via keypoints.

Medical image analysis Sep 13, 2023
We present KeyMorph, a deep learning-based image registration framework that relies on automatically detecting corresponding keypoints. State-of-the-art deep learning methods for registration often are not robust to large misalignments, are not inter...
Magnetic Resonance Imaging Neuroimaging Deep Learning Brain Humans Image Processing, Computer-Assisted
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iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease.

PLoS computational biology Sep 11, 2023
Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing e...
Learning Deep Learning Records Brain
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Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.

European journal of nuclear medicine and molecular imaging Sep 6, 2023
PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult t...
Humans Brain Positron-Emission Tomography Quality Improvement Phantoms, Imaging Deep Learning Image Processing, Computer-Assisted
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Deep learning for automated detection of generalized paroxysmal fast activity in Lennox-Gastaut syndrome.

Epilepsy & behavior : E&B Sep 6, 2023
OBJECTIVES: Generalized paroxysmal fast activity (GPFA) is a key electroencephalographic (EEG) feature of Lennox-Gastaut Syndrome (LGS). Automated analysis of scalp EEG has been successful in detecting more typical abnormalities. Automatic detection ...
Lennox Gastaut Syndrome Deep Learning Electroencephalography Humans Brain
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