AIMC Topic: Brain

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Asymmetric Adaptive Heterogeneous Network for Multi-Modality Medical Image Segmentation.

IEEE transactions on medical imaging Apr 3, 2025
Existing studies of multi-modality medical image segmentation tend to aggregate all modalities without discrimination and employ multiple symmetric encoders or decoders for feature extraction and fusion. They often overlook the different contribution...
Multimodal Imaging Databases, Factual Humans Brain Neural Networks, Computer Algorithms Image Processing, Computer-Assisted
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Amyloid-β Deposition Prediction With Large Language Model Driven and Task-Oriented Learning of Brain Functional Networks.

IEEE transactions on medical imaging Apr 3, 2025
Amyloid- positron emission tomography can reflect the Amyloid- protein deposition in the brain and thus serves as one of the golden standards for Alzheimer's disease (AD) diagnosis. However, its practical cost and high radioactivity hinder its applic...
Alzheimer Disease Positron-Emission Tomography Image Interpretation, Computer-Assisted Deep Learning Magnetic Resonance Imaging Humans Amyloid beta-Peptides Brain Female Large Language Models Aged Male
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Exploring Contrastive Pre-Training for Domain Connections in Medical Image Segmentation.

IEEE transactions on medical imaging Apr 3, 2025
Unsupervised domain adaptation (UDA) in medical image segmentation aims to improve the generalization of deep models by alleviating domain gaps caused by inconsistency across equipment, imaging protocols, and patient conditions. However, existing UDA...
Unsupervised Machine Learning Brain Humans Algorithms Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Tackling Modality-Heterogeneous Client Drift Holistically for Heterogeneous Multimodal Federated Learning.

IEEE transactions on medical imaging Apr 3, 2025
Multimodal Federated Learning (MFL) has emerged as a collaborative paradigm for training models across decentralized devices, harnessing various data modalities to facilitate effective learning while respecting data ownership. In this realm, notably,...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Federated Learning Algorithms Brain Tomography, X-Ray Computed Humans Machine Learning
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PASS: Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation.

IEEE transactions on medical imaging Apr 3, 2025
Test-time adaptation (TTA) has emerged as a promising paradigm to handle the domain shifts at test time for medical images from different institutions without using extra training data. However, existing TTA solutions for segmentation tasks suffer fr...
Brain Image Processing, Computer-Assisted Humans Deep Learning Semantics Algorithms
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POUR-Net: A Population-Prior-Aided Over-Under-Representation Network for Low-Count PET Attenuation Map Generation.

IEEE transactions on medical imaging Apr 3, 2025
Low-dose PET offers a valuable means of minimizing radiation exposure in PET imaging. However, the prevalent practice of employing additional CT scans for generating attenuation maps ( -map) for PET attenuation correction significantly elevates radia...
Image Processing, Computer-Assisted Positron-Emission Tomography Neural Networks, Computer Algorithms Brain Humans
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Sulforaphane protects developing neural networks from VPA-induced synaptic alterations.

Molecular psychiatry Apr 2, 2025
Prenatal brain development is particularly sensitive to chemicals that can disrupt synapse formation and cause neurodevelopmental disorders. In most cases, such chemicals increase cellular oxidative stress. For example, prenatal exposure to the anti-...
Antioxidants Disease Models, Animal Mice, Inbred C57BL Male Humans Nerve Net Oxidative Stress Autism Spectrum Disorder NF-E2-Related Factor 2 Mice Female Isothiocyanates Neurons Animals Valproic Acid Brain Synapses Sulfoxides Pregnancy
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Random forest and Shapley Additive exPlanations predict oxytocin targeted effects on brain functional networks involved in salience and sensorimotor processing, in a randomized clinical trial in autism.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Apr 2, 2025
Intranasal oxytocin (IN-OXT) has shown some promises in rescuing social deficits in autism spectrum disorder (ASD) as well as some inconsistencies in long-term trials. We conducted a target engagement study to study the precise effects of different d...
Brain Young Adult Adult Male Humans Autism Spectrum Disorder Administration, Intranasal Random Forest Magnetic Resonance Imaging Oxytocin Dose-Response Relationship, Drug Nerve Net Double-Blind Method
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Leveraging Physics-Based Synthetic MR Images and Deep Transfer Learning for Artifact Reduction in Echo-Planar Imaging.

AJNR. American journal of neuroradiology Apr 2, 2025
BACKGOUND AND PURPOSE: This study utilizes a physics-based approach to synthesize realistic MR artifacts and train a deep learning generative adversarial network (GAN) for use in artifact reduction on EPI, a crucial neuroimaging sequence with high ac...
Magnetic Resonance Imaging Artifacts Echo-Planar Imaging Middle Aged Humans Deep Learning Brain Neoplasms Image Processing, Computer-Assisted Male Brain Female
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Comprehensive Segmentation of Gray Matter Structures on T1-Weighted Brain MRI: A Comparative Study of Convolutional Neural Network, Convolutional Neural Network Hybrid-Transformer or -Mamba Architectures.

AJNR. American journal of neuroradiology Apr 2, 2025
BACKGROUND AND PURPOSE: Recent advances in deep learning have shown promising results in medical image analysis and segmentation. However, most brain MRI segmentation models are limited by the size of their data sets and/or the number of structures t...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Alzheimer Disease Middle Aged Deep Learning Convolutional Neural Networks Gray Matter Humans Neural Networks, Computer Brain Female Aged Male
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