AIMC Topic: Brain

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VCU-Net: a vascular convolutional network with feature splicing for cerebrovascular image segmentation.

Medical & biological engineering & computing Oct 25, 2024
Cerebrovascular image segmentation is one of the crucial tasks in the field of biomedical image processing. Due to the variable morphology of cerebral blood vessels, the traditional convolutional kernel is weak in perceiving the structure of elongate...
Brain Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Deep learning corrects artifacts in RASER MRI profiles.

Magnetic resonance imaging Oct 24, 2024
A newly developed magnetic resonance imaging (MRI) approach is based on "Radiowave amplification by the stimulated emission of radiation" (RASER). RASER MRI potentially allows for higher resolution, is inherently background-free, and does not require...
Brain Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Magnetic Resonance Imaging Artifacts Phantoms, Imaging Radio Waves
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Robust brain MRI image classification with SIBOW-SVM.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Oct 24, 2024
Primary Central Nervous System tumors in the brain are among the most aggressive diseases affecting humans. Early detection and classification of brain tumor types, whether benign or malignant, glial or non-glial, is critical for cancer prevention an...
Humans Neural Networks, Computer Algorithms Brain Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Brain Neoplasms Deep Learning Support Vector Machine
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Exploring potential ADHD biomarkers through advanced machine learning: An examination of audiovisual integration networks.

Computers in biology and medicine Oct 23, 2024
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition marked by inattention and impulsivity, linked to disruptions in functional brain connectivity and structural alterations in large-scale brain networks. Although sensory...
Visual Perception Attention Deficit Disorder with Hyperactivity Auditory Perception Child Magnetic Resonance Imaging Nerve Net Machine Learning Biomarkers Brain Female Male Adolescent Humans
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Deep-Learning-Based Segmentation of Cells and Analysis (DL-SCAN).

Biomolecules Oct 23, 2024
With the recent surge in the development of highly selective probes, fluorescence microscopy has become one of the most widely used approaches to studying cellular properties and signaling in living cells and tissues. Traditionally, microscopy image ...
Sodium Animals Signal-To-Noise Ratio Deep Learning Image Processing, Computer-Assisted Mice Microscopy, Fluorescence Software Astrocytes Brain Neurons Fluorescent Dyes Calcium
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Resting-State Electroencephalogram Depression Diagnosis Based on Traditional Machine Learning and Deep Learning: A Comparative Analysis.

Sensors (Basel, Switzerland) Oct 23, 2024
The global prevalence of Major Depressive Disorder (MDD) is increasing at an alarming rate, underscoring the urgent need for timely and accurate diagnoses to facilitate effective interventions and treatments. Electroencephalography remains a widely u...
Deep Learning Electroencephalography Machine Learning Brain Depressive Disorder, Major Humans
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Automated detection of motion artifacts in brain MR images using deep learning.

NMR in biomedicine Oct 22, 2024
Quality assessment, including inspecting the images for artifacts, is a critical step during magnetic resonance imaging (MRI) data acquisition to ensure data quality and downstream analysis or interpretation success. This study demonstrates a deep le...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Motion Artifacts Automation Humans Brain
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Structure preservation constraints for unsupervised domain adaptation intracranial vessel segmentation.

Medical & biological engineering & computing Oct 21, 2024
Unsupervised domain adaptation (UDA) has received interest as a means to alleviate the burden of data annotation. Nevertheless, existing UDA segmentation methods exhibit performance degradation in fine intracranial vessel segmentation tasks due to th...
Humans Image Processing, Computer-Assisted Unsupervised Machine Learning Magnetic Resonance Angiography Computed Tomography Angiography Neural Networks, Computer Algorithms Brain
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3D CNN for neuropsychiatry: Predicting Autism with interpretable Deep Learning applied to minimally preprocessed structural MRI data.

PloS one Oct 21, 2024
Predictive modeling approaches are enabling progress toward robust and reproducible brain-based markers of neuropsychiatric conditions by leveraging the power of multivariate analyses of large datasets. While deep learning (DL) offers another promisi...
Neuropsychiatry Deep Learning Female Imaging, Three-Dimensional Adolescent Humans Magnetic Resonance Imaging Adult Child Neural Networks, Computer Autistic Disorder Male Brain
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Machine learning models of cerebral oxygenation (rcSO) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.

The Journal of physiology Oct 19, 2024
The present study was designed to test the potential utility of regional cerebral oxygen saturation (rcSO) in detecting term infants with brain injury. The study also examined whether quantitative rcSO features are associated with grade of hypoxic is...
Oxygen Saturation Hypoxia-Ischemia, Brain Magnetic Resonance Imaging Brain Injuries Oxygen Machine Learning Prospective Studies Brain Female Infant, Newborn Male Humans
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