AIMC Topic: Brain

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Impaired interhemispheric synchrony in patients with iridocyclitis and classification using machine learning: an fMRI study.

Frontiers in immunology Dec 16, 2024
BACKGROUND: This study examined the interhemispheric integration function pattern in patients with iridocyclitis utilizing the voxel-mirrored homotopic connectivity (VMHC) technique. Additionally, we investigated the ability of VMHC results to distin...
Middle Aged Female Humans Support Vector Machine Adult Magnetic Resonance Imaging Machine Learning Male Brain Iridocyclitis Brain Mapping
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Automatic Segmentation of Sylvian Fissure in Brain Ultrasound Images of Pre-Term Infants Using Deep Learning Models.

Ultrasound in medicine & biology Dec 15, 2024
OBJECTIVE: Segmentation of brain sulci in pre-term infants is crucial for monitoring their development. While magnetic resonance imaging has been used for this purpose, cranial ultrasound (cUS) is the primary imaging technique used in clinical practi...
Deep Learning Ultrasonography Infant, Premature Female Infant, Newborn Male Humans Brain
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Conditional generative diffusion deep learning for accelerated diffusion tensor and kurtosis imaging.

Magnetic resonance imaging Dec 13, 2024
PURPOSE: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model designed to produce high-quality diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics from a reduced set of diffusion-weighted...
Signal-To-Noise Ratio Connectome Diffusion Tensor Imaging Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Anisotropy Diffusion Magnetic Resonance Imaging Humans Algorithms Brain Adult Male Female Reproducibility of Results
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A Context-Dependent CNN-Based Framework for Multiple Sclerosis Segmentation in MRI.

International journal of neural systems Dec 13, 2024
Despite several automated strategies for identification/segmentation of Multiple Sclerosis (MS) lesions in Magnetic Resonance Imaging (MRI) being developed, they consistently fall short when compared to the performance of human experts. This emphasiz...
Multiple Sclerosis Image Interpretation, Computer-Assisted Neural Networks, Computer Brain Magnetic Resonance Imaging Humans
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Adapting to time: Why nature may have evolved a diverse set of neurons.

PLoS computational biology Dec 13, 2024
Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explor...
Adaptation, Physiological Biological Evolution Brain Neurons Humans Models, Neurological Nerve Net Animals Neural Networks, Computer Action Potentials Computational Biology
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Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.

PLoS computational biology Dec 13, 2024
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still u...
Neural Networks, Computer Algorithms Brain Computer Simulation Humans Action Potentials Neurons Nerve Net Adaptation, Physiological Animals Computational Biology Models, Neurological
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A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.

PeerJ Dec 13, 2024
BACKGROUND: Alzheimer's Disease (AD) poses a major challenge as a neurodegenerative disorder, and early detection is critical for effective intervention. Magnetic resonance imaging (MRI) is a critical tool in AD research due to its availability and c...
Aged Alzheimer Disease Humans Aged, 80 and over Early Diagnosis Biomarkers Machine Learning Male Neuroimaging Brain Cognitive Dysfunction Female Magnetic Resonance Imaging Bayes Theorem
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Contrastive machine learning reveals species -shared and -specific brain functional architecture.

Medical image analysis Dec 12, 2024
A deep comparative analysis of brain functional connectome across species in primates has the potential to yield valuable insights for both scientific and clinical applications. However, the interspecies commonality and differences are inherently ent...
Animals Magnetic Resonance Imaging Humans Species Specificity Machine Learning Brain Connectome Macaca
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Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Dec 12, 2024
OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerative diseases characterized by altered brain functional connectivity (FC), affecting over 100 million people worldwide. This study aims to identify disti...
Machine Learning Brain Female Middle Aged Support Vector Machine Aged Male Humans Electroencephalography Nerve Net Alzheimer Disease Frontotemporal Dementia
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Where, why, and how is bias learned in medical image analysis models? A study of bias encoding within convolutional networks using synthetic data.

EBioMedicine Dec 12, 2024
BACKGROUND: Understanding the mechanisms of algorithmic bias is highly challenging due to the complexity and uncertainty of how various unknown sources of bias impact deep learning models trained with medical images. This study aims to bridge this kn...
Algorithms Databases, Factual Brain Convolutional Neural Networks Humans Image Processing, Computer-Assisted Bias Magnetic Resonance Imaging Diagnostic Imaging
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