AIMC Topic: Brain

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Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

Scientific reports Feb 9, 2025
To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed...
Brain Computer Simulation Deep Learning Humans Neural Networks, Computer Signal-To-Noise Ratio Monte Carlo Method Image Processing, Computer-Assisted Magnetic Resonance Imaging Cost-Benefit Analysis
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Using deep feature distances for evaluating the perceptual quality of MR image reconstructions.

Magnetic resonance in medicine Feb 8, 2025
PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceived diagnostic IQ. Here, we develop and explore deep feature distances (DFDs)-distances computed in a lower-dimensional feature space encoded by a convo...
Humans Neural Networks, Computer Algorithms Brain Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Signal-To-Noise Ratio
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Alzheimer's disease classification using hybrid loss Psi-Net segmentation and a new hybrid network model.

Computational biology and chemistry Feb 8, 2025
Alzheimer's disease (AD) is a type of brain disorder that is becoming more prevalent worldwide. It is a progressive and irreversible condition that gradually impairs memory and cognitive abilities, eventually making it difficult to perform even basic...
Brain Humans Image Processing, Computer-Assisted Neural Networks, Computer Alzheimer Disease Algorithms
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DeepReducer: A linear transformer-based model for MEG denoising.

NeuroImage Feb 8, 2025
Measuring event-related magnetic fields (ERFs) in magnetoencephalography (MEG) is crucial for investigating perceptual and cognitive information processing in both neuroscience research and clinical practice. However, the magnitude of the ERF in cort...
Magnetoencephalography Humans Signal Processing, Computer-Assisted Brain Deep Learning Artifacts Signal-To-Noise Ratio
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Characterizing drivers of change in intraoperative cerebral saturation using supervised machine learning.

Journal of clinical monitoring and computing Feb 7, 2025
Regional cerebral oxygen saturation (rSO) is used to monitor cerebral perfusion with emerging evidence that optimization of rSO may improve neurological and non-neurological outcomes. To manipulate rSO an understanding of the variables that drive its...
Humans Machine Learning Algorithms Brain Oximetry Carbon Dioxide Oxygen Saturation Cerebrovascular Circulation Adult Male Spectroscopy, Near-Infrared Middle Aged Female Hemodynamics Signal Processing, Computer-Assisted Reproducibility of Results Monitoring, Intraoperative Supervised Machine Learning Aged ROC Curve Oxygen
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Deep graph embedding based on Laplacian eigenmaps for MR fingerprinting reconstruction.

Medical image analysis Feb 7, 2025
Magnetic resonance fingerprinting (MRF) is a promising technique for fast quantitative imaging of multiple tissue parameters. However, the highly undersampled schemes utilized in MRF typically lead to noticeable aliasing artifacts in reconstructed im...
Algorithms Brain Humans Artifacts Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Enhanced EEG-based cognitive workload detection using RADWT and machine learning.

Neuroscience Feb 7, 2025
Understanding cognitive workload improves learning performance and provides insights into human cognitive processes. Estimating cognitive workload finds practical applications in adaptive learning systems, brain-computer interfaces, and cognitive mon...
Support Vector Machine Humans Machine Learning Electroencephalography Workload Adult Wavelet Analysis Brain Male Female Cognition Young Adult
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ECA-FusionNet: a hybrid EEG-fNIRS signals network for MI classification.

Journal of neural engineering Feb 7, 2025
. Among all BCI paradigms, motion imagery (MI) has gained favor among researchers because it allows users to control external devices by imagining movements rather than actually performing actions. This property holds important promise for clinical a...
Brain Spectroscopy, Near-Infrared Electroencephalography Humans Neural Networks, Computer Brain-Computer Interfaces Movement Imagination
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Predicting cognitive decline: Deep-learning reveals subtle brain changes in pre-MCI stage.

The journal of prevention of Alzheimer's disease Feb 6, 2025
BACKGROUND: Mild cognitive impairment (MCI) and preclinical MCI (e.g., subjective cognitive decline, SCD) are considered risk states of dementia, such as Alzheimer's Disease (AD). However, it is challenging to accurately predict conversion from norma...
Neuroimaging Longitudinal Studies Magnetic Resonance Imaging Alzheimer Disease Female Aged Aged, 80 and over Deep Learning Humans Cognitive Dysfunction Brain Male Disease Progression
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DeepPrep: an accelerated, scalable and robust pipeline for neuroimaging preprocessing empowered by deep learning.

Nature methods Feb 6, 2025
Neuroimaging has entered the era of big data. However, the advancement of preprocessing pipelines falls behind the rapid expansion of data volume, causing substantial computational challenges. Here we present DeepPrep, a pipeline empowered by deep le...
Neuroimaging Algorithms Brain Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Workflow Humans Software
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