AIMC Topic: Brain

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Exploring the performance of implicit neural representations for brain image registration.

Scientific reports Oct 13, 2023
Pairwise image registration is a necessary prerequisite for brain image comparison and data integration in neuroscience and radiology. In this work, we explore the efficacy of implicit neural representations (INRs) in improving the performance of bra...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Neural Networks, Computer
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Unsupervised deep learning registration model for multimodal brain images.

Journal of applied clinical medical physics Oct 12, 2023
Multimodal image registration is a key for many clinical image-guided interventions. However, it is a challenging task because of complicated and unknown relationships between different modalities. Currently, deep supervised learning is the state-of-...
Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Brain
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U-Net based vessel segmentation for murine brains with small micro-magnetic resonance imaging reference datasets.

PloS one Oct 12, 2023
Identification and quantitative segmentation of individual blood vessels in mice visualized with preclinical imaging techniques is a tedious, manual or semiautomated task that can require weeks of reviewing hundreds of levels of individual data sets....
Animals Neural Networks, Computer Image Processing, Computer-Assisted Brain Mice Magnetic Resonance Imaging
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Complexity in structural and functional brain networks. Comment on "Structure and function in artificial, zebrafish and human neural networks" by Ji et al.

Physics of life reviews Oct 11, 2023
Brain Animals Zebrafish Humans Neural Networks, Computer Head
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A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing.

Nature communications Oct 11, 2023
Neuromorphic computing aims to emulate the computing processes of the brain by replicating the functions of biological neural networks using electronic counterparts. One promising approach is dendritic computing, which takes inspiration from the mult...
Neural Networks, Computer Computers Memory, Short-Term Electronics Brain Humans
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Multimodal hybrid convolutional neural network based brain tumor grade classification.

BMC bioinformatics Oct 10, 2023
An abnormal growth or fatty mass of cells in the brain is called a tumor. They can be either healthy (normal) or become cancerous, depending on the structure of their cells. This can result in increased pressure within the cranium, potentially causin...
Magnetic Resonance Imaging Tomography, X-Ray Computed Brain Neoplasms Neural Networks, Computer Brain Humans
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3D Ultrasonic Brain Imaging with Deep Learning Based on Fully Convolutional Networks.

Sensors (Basel, Switzerland) Oct 9, 2023
Compared to magnetic resonance imaging (MRI) and X-ray computed tomography (CT), ultrasound imaging is safer, faster, and more widely applicable. However, the use of conventional ultrasound in transcranial brain imaging for adults is predominantly hi...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Adult Deep Learning Ultrasonics Neuroimaging Humans Brain
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Bayesian learning from multi-way EEG feedback for robot navigation and target identification.

Scientific reports Oct 7, 2023
Many brain-computer interfaces require a high mental workload. Recent research has shown that this could be greatly alleviated through machine learning, inferring user intentions via reactive brain responses. These signals are generated spontaneously...
Brain-Computer Interfaces Neurofeedback Bayes Theorem Electroencephalography Brain Robotics
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Global and Regional Deep Learning Models for Multiple Sclerosis Stratification From MRI.

Journal of magnetic resonance imaging : JMRI Oct 6, 2023
BACKGROUND: The combination of anatomical MRI and deep learning-based methods such as convolutional neural networks (CNNs) is a promising strategy to build predictive models of multiple sclerosis (MS) prognosis. However, studies assessing the effect ...
Magnetic Resonance Imaging Multiple Sclerosis ROC Curve Image Processing, Computer-Assisted Adult Male Middle Aged Deep Learning Female Reproducibility of Results Prognosis Retrospective Studies Neural Networks, Computer Brain Humans
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Quantitative Electroencephalography Objectivity and Reliability in the Diagnosis and Management of Traumatic Brain Injury: A Systematic Review.

Clinical EEG and neuroscience Oct 4, 2023
Persons with a history of traumatic brain injury (TBI) may exhibit short- and long-term cognitive deficits as well as psychiatric symptoms. These symptoms often reflect functional anomalies in the brain that are not detected by standard neuroimaging...
Humans Reproducibility of Results Brain Injuries, Traumatic Electroencephalography Machine Learning Brain
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