AIMC Topic: Brain
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Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence.
International journal of molecular sciences
Apr 11, 2024
Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating synapses on large populations of CNS neurons. PNN undergo structural changes in schizophrenia, epilepsy, Alzheimer's disease, stroke, post-traumatic co...
Spinet-QSM: model-based deep learning with schatten p-norm regularization for improved quantitative susceptibility mapping.
Magma (New York, N.Y.)
Apr 10, 2024
OBJECTIVE: Quantitative susceptibility mapping (QSM) provides an estimate of the magnetic susceptibility of tissue using magnetic resonance (MR) phase measurements. The tissue magnetic susceptibility (source) from the measured magnetic field distribu...
Enhancing cross-subject EEG emotion recognition through multi-source manifold metric transfer learning.
Computers in biology and medicine
Apr 9, 2024
Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptation challenges in affective brain-computer interfaces (aBCI). However, previous TL methods usually use a stationary distance, such as Euclidean distanc...
An efficient Parkinson's disease detection framework: Leveraging time-frequency representation and AlexNet convolutional neural network.
Computers in biology and medicine
Apr 9, 2024
Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting the quality of life of over 10 million individuals worldwide. Early diagnosis is crucial for timely intervention and better patient outcomes. Electroencephalogram (EEG) si...
Viability leads to the emergence of gait transitions in learning agile quadrupedal locomotion on challenging terrains.
Nature communications
Apr 9, 2024
Quadruped animals are capable of seamless transitions between different gaits. While energy efficiency appears to be one of the reasons for changing gaits, other determinant factors likely play a role too, including terrain properties. In this articl...
A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions.
Scientific reports
Apr 8, 2024
This work presents a deep learning approach for rapid and accurate muscle water T with subject-specific fat T calibration using multi-spin-echo acquisitions. This method addresses the computational limitations of conventional bi-component Extended Ph...
Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach.
AJNR. American journal of neuroradiology
Apr 8, 2024
BACKGROUND AND PURPOSE: Spontaneous intracranial hypotension is an increasingly recognized condition. Spontaneous intracranial hypotension is caused by a CSF leak, which is commonly related to a CSF-venous fistula. In patients with spontaneous intrac...
Connectional-style-guided contextual representation learning for brain disease diagnosis.
Neural networks : the official journal of the International Neural Network Society
Apr 7, 2024
Structural magnetic resonance imaging (sMRI) has shown great clinical value and has been widely used in deep learning (DL) based computer-aided brain disease diagnosis. Previous DL-based approaches focused on local shapes and textures in brain sMRI t...
Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning.
Medical image analysis
Apr 6, 2024
Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and cli...
Discourse- and lesion-based aphasia quotient estimation using machine learning.
NeuroImage. Clinical
Apr 6, 2024
Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia as...
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