AIMC Topic: Brain
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Trends in brain MRI and CP association using deep learning.
La Radiologia medica
Oct 10, 2024
Cerebral palsy (CP) is a neurological disorder that dissipates body posture and impairs motor functions. It may lead to an intellectual disability and affect the quality of life. Early intervention is critical and challenging due to the uncooperative...
Knowledge-driven multi-graph convolutional network for brain network analysis and potential biomarker discovery.
Medical image analysis
Oct 9, 2024
In brain network analysis, individual-level data can provide biological features of individuals, while population-level data can provide demographic information of populations. However, existing methods mostly utilize either individual- or population...
Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages.
Nature methods
Oct 7, 2024
Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we ha...
A deep learning approach for non-invasive Alzheimer's monitoring using microwave radar data.
Neural networks : the official journal of the International Neural Network Society
Oct 5, 2024
Over 50 million people globally suffer from Alzheimer's disease (AD), emphasizing the need for efficient, early diagnostic tools. Traditional methods like Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scans are expensive, bulky, and s...
MG-Net: A fetal brain tissue segmentation method based on multiscale feature fusion and graph convolution attention mechanisms.
Computer methods and programs in biomedicine
Oct 5, 2024
BACKGROUND AND OBJECTIVE: Fetal brain tissue segmentation provides foundational support for comprehensively understanding the neurodevelopment of normal and congenital disease-affected fetuses. Manual labeling is very time-consuming, and automated se...
Machine learning based classification of excessive smartphone users via neuronal cue reactivity.
Psychiatry research. Neuroimaging
Oct 2, 2024
Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data an...
Deep Learning-Based Synthetic Computed Tomography for Low-Field Brain Magnetic Resonance-Guided Radiation Therapy.
International journal of radiation oncology, biology, physics
Oct 1, 2024
PURPOSE: Magnetic resonance (MR)-guided radiation therapy enables online adaptation to address intra- and interfractional changes. To address the need of high-fidelity synthetic computed tomography (synCT) required for dose calculation, we developed ...
Detection of Low Resilience Using Data-Driven Effective Connectivity Measures.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 1, 2024
Conventional thresholding techniques for graph theory analysis, such as absolute, proportional and mean degree, have often been used in characterizing human brain networks under different mental disorders, such as mental stress. However, these approa...
Transformer-based approaches for neuroimaging: an in-depth review of their role in classification and regression tasks.
Reviews in the neurosciences
Sep 30, 2024
In the ever-evolving landscape of deep learning (DL), the transformer model emerges as a formidable neural network architecture, gaining significant traction in neuroimaging-based classification and regression tasks. This paper presents an extensive ...
Classification of psychosis spectrum disorders using graph convolutional networks with structurally constrained functional connectomes.
Neural networks : the official journal of the International Neural Network Society
Sep 30, 2024
This article considers the problem of classifying individuals in a dataset of diverse psychosis spectrum conditions, including persons with subsyndromal psychotic-like experiences (PLEs) and healthy controls. This task is more challenging than the tr...
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