AIMC Topic: Brain

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The emergence of machine learning in auditory neural impairment: A systematic review.

Neuroscience letters
Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (E...

Automatic Symmetry Detection From Brain MRI Based on a 2-Channel Convolutional Neural Network.

IEEE transactions on cybernetics
Symmetry detection is a method to extract the ideal mid-sagittal plane (MSP) from brain magnetic resonance (MR) images, which can significantly improve the diagnostic accuracy of brain diseases. In this article, we propose an automatic symmetry detec...

The Effect of Deep Learning-Based QSM Magnetic Resonance Imaging on the Subthalamic Nucleus.

Journal of healthcare engineering
In order to study the influence of quantitative magnetic susceptibility mapping (QSM) on them. A 2.5D Attention U-Net Network based on multiple input and multiple output, a method for segmenting RN, SN, and STN regions in high-resolution QSM images i...

The whole brain architecture approach: Accelerating the development of artificial general intelligence by referring to the brain.

Neural networks : the official journal of the International Neural Network Society
The vastness of the design space that is created by the combination of numerous computational mechanisms, including machine learning, is an obstacle to creating artificial general intelligence (AGI). Brain-inspired AGI development; that is, the reduc...

Performance improvement of weakly supervised fully convolutional networks by skip connections for brain structure segmentation.

Medical physics
PURPOSE: For the planning and navigation of neurosurgery, we have developed a fully convolutional network (FCN)-based method for brain structure segmentation on magnetic resonance (MR) images. The capability of an FCN depends on the quality of the tr...

A New General Maximum Intensity Projection Technology via the Hybrid of U-Net and Radial Basis Function Neural Network.

Journal of digital imaging
Maximum intensity projection (MIP) technology is a computer visualization method that projects three-dimensional spatial data on a visualization plane. According to the specific purposes, the specific lab thickness and direction can be selected. This...

Unified AI framework to uncover deep interrelationships between gene expression and Alzheimer's disease neuropathologies.

Nature communications
Deep neural networks (DNNs) capture complex relationships among variables, however, because they require copious samples, their potential has yet to be fully tapped for understanding relationships between gene expression and human phenotypes. Here we...

MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation.

NeuroImage
The annotation of brain lesion images is a key step in clinical diagnosis and treatment of a wide spectrum of brain diseases. In recent years, segmentation methods based on deep learning have gained unprecedented popularity, leveraging a large amount...

Dual coding of knowledge in the human brain.

Trends in cognitive sciences
How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human language, neurocognitive models of knowledge have been dominated by sensory embodiment, in which knowl...

A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps.

Sensors (Basel, Switzerland)
Neuromorphic hardware systems have been gaining ever-increasing focus in many embedded applications as they use a brain-inspired, energy-efficient spiking neural network (SNN) model that closely mimics the human cortex mechanism by communicating and ...