AIMC Topic: Brain

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Inductive biases of neural network modularity in spatial navigation.

Science advances Jul 19, 2024
The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architect...
Learning Animals Models, Neurological Bayes Theorem Nerve Net Spatial Navigation Humans Neural Networks, Computer Brain
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Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI.

IEEE transactions on bio-medical engineering Jul 18, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in the brain and is widely used for brain disorder analysis. Previous studies focus on extracting fMRI representations using machine/deep learning...
Machine Learning Algorithms Brain Image Processing, Computer-Assisted Female Humans Magnetic Resonance Imaging Adult Neural Networks, Computer Brain Mapping Male
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Spatial-Temporal Dynamic Hypergraph Information Bottleneck for Brain Network Classification.

International journal of neural systems Jul 17, 2024
Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic brain network classification tasks, owing to their ability to directly capture crucial information in non-Euclidean structures. However, two primary challenges per...
Nerve Net Humans Neural Networks, Computer Brain Information Theory
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Neurological insights into brain-targeted cancer therapy and bioinspired microrobots.

Drug discovery today Jul 17, 2024
Cancer, a multifaceted and pernicious disease, continuously challenges medicine, requiring innovative treatments. Brain cancers pose unique and daunting challenges due to the intricacies of the central nervous system and the blood-brain barrier. In t...
Blood-Brain Barrier Animals Drug Delivery Systems Antineoplastic Agents Brain Neoplasms Robotics Humans Brain Precision Medicine
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XAI-Based Assessment of the AMURA Model for Detecting Amyloid-β and Tau Microstructural Signatures in Alzheimer's Disease.

IEEE journal of translational engineering in health and medicine Jul 17, 2024
Brain microstructural changes already occur in the earliest phases of Alzheimer's disease (AD) as evidenced in diffusion magnetic resonance imaging (dMRI) literature. This study investigates the potential of the novel dMRI Apparent Measures Using Red...
Amyloid beta-Peptides Alzheimer Disease Image Interpretation, Computer-Assisted Aged tau Proteins Male Humans Diffusion Magnetic Resonance Imaging Support Vector Machine Brain Female
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Efficient segmentation of active and inactive plaques in FLAIR-images using DeepLabV3Plus SE with efficientnetb0 backbone in multiple sclerosis.

Scientific reports Jul 15, 2024
This research paper introduces an efficient approach for the segmentation of active and inactive plaques within Fluid-attenuated inversion recovery (FLAIR) images, employing a convolutional neural network (CNN) model known as DeepLabV3Plus SE with th...
Magnetic Resonance Imaging Multiple Sclerosis Middle Aged Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Brain Female Adult Cross-Sectional Studies Humans Male
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Dual domain distribution disruption with semantics preservation: Unsupervised domain adaptation for medical image segmentation.

Medical image analysis Jul 14, 2024
Recent unsupervised domain adaptation (UDA) methods in medical image segmentation commonly utilize Generative Adversarial Networks (GANs) for domain translation. However, the translated images often exhibit a distribution deviation from the ideal due...
Image Processing, Computer-Assisted Unsupervised Machine Learning Semantics Humans Algorithms Brain Male
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Disentangling brain atrophy heterogeneity in Alzheimer's disease: A deep self-supervised approach with interpretable latent space.

NeuroImage Jul 14, 2024
Alzheimer's disease (AD) is heterogeneous, but existing methods for capturing this heterogeneity through dimensionality reduction and unsupervised clustering have limitations when it comes to extracting intricate atrophy patterns. In this study, we p...
Alzheimer Disease Atrophy Deep Learning Magnetic Resonance Imaging Supervised Machine Learning Brain Female Aged Aged, 80 and over Male Disease Progression Humans
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Motion Artifact Detection for T1-Weighted Brain MR Images Using Convolutional Neural Networks.

International journal of neural systems Jul 12, 2024
Quality assessment (QA) of magnetic resonance imaging (MRI) encompasses several factors such as noise, contrast, homogeneity, and imaging artifacts. Quality evaluation is often not standardized and relies on the expertise, and vigilance of the person...
Head Movements Male Deep Learning Image Processing, Computer-Assisted Brain Magnetic Resonance Imaging Female Motion Adult Artifacts Humans Neural Networks, Computer
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deepbet: Fast brain extraction of T1-weighted MRI using Convolutional Neural Networks.

Computers in biology and medicine Jul 12, 2024
BACKGROUND: Brain extraction in magnetic resonance imaging (MRI) data is an important segmentation step in many neuroimaging preprocessing pipelines. Image segmentation is one of the research fields in which deep learning had the biggest impact in re...
Humans Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Databases, Factual Brain Neuroimaging
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