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Brain Cortical Surface Registration with Anatomical Atlas Constraints
This work presents a novel cortical surface registration framework by using the whole anatomical atlas structures as correspondence constraints,...
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Continuous Longitudinal Fetus Brain Atlas Construction via Implicit Neural Representation
Longitudinal fetal brain atlas is a powerful tool for understanding and characterizing the complex process of fetus brain development. Existing fetus...
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Multi-atlas Representations Based on Graph Convolutional Networks for Autism Spectrum Disorder Diagnosis
Constructing functional connectivity (FC) based on brain atlas is a common approach to autism spectrum disorder (ASD) diagnosis, which is a...
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Multi-atlas subcortical segmentation: an orchestration of 3D fully convolutional network and generalized mixture function
To accurately segment subcortical structures and therefore profit for numerous neuroimaging applications, we proposed a multi-atlas subcortical...
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A robust combined weighted label fusion in multi-atlas pancreas segmentation
Multi-atlas segmentation frameworks have proved to be a top-method as its good performance in medical image segmentation, which mainly consists of...
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Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas Using a Contrastively Learned Semantic Space
Registering mouse brain microscopy images to a reference atlas is crucial to determine the locations of anatomical structures in the brain, which is...
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Towards a 4D Spatio-Temporal Atlas of the Embryonic and Fetal Brain Using a Deep Learning Approach for Groupwise Image Registration
Brain development during the first trimester is of crucial importance for current and future health of the fetus, and therefore the availability of a...
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Brain Diffuser: An End-to-End Brain Image to Brain Network Pipeline
Brain network analysis is essential for diagnosing and intervention for Alzheimer’s disease (AD). However, previous research relied primarily on...
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Groupwise Image Registration with Atlas of Multiple Resolutions Refined at Test Phase
Groupwise image registration (GIR) is a fundamental task that facilitates the simultaneous deformation of a group of subjects towards a specified or...
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Multi-atlas Graph Convolutional Networks and Convolutional Recurrent Neural Networks-Based Ensemble Learning for Classification of Autism Spectrum Disorders
Autism spectrum disorder (ASD) has an influence on social conversation and interaction, as well as encouraging people to engage in repetitive...
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Investigating the impact of standard brain atlases and connectivity measures on the accuracy of ADHD detection from fMRI data using deep learning
Inattention, hyperactivity, and impulsivity are among the symptoms of Attention Deficit Hyperactivity Syndrome (ADHD). This brain disorder cannot...
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Learning Ontology-Based Hierarchical Structural Relationship for Whole Brain Segmentation
Whole brain segmentation is vital for a variety of anatomical investigations in brain development, aging, and degradation. It is nevertheless...
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Virtual reality technologies for training tourism company managers: A case study of the ATLAS platform
The study investigates the impact of virtual reality technologies on the training of managers in the tourism industry using the ATLAS platform. A...
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CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI
Fetal Magnetic Resonance Imaging (MRI) is used in prenatal diagnosis and to assess early brain development. Accurate segmentation of the different...
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Multimodal Fusion of Brain Imaging Data: Methods and Applications
Neuroimaging data typically include multiple modalities, such as structural or functional magnetic resonance imaging, diffusion tensor imaging, and...
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Regionalized Infant Brain Cortical Development Based on Multi-view, High-Level fMRI Fingerprint
The human brain demonstrates higher spatial and functional heterogeneity during the first two postnatal years than any other period of life. Infant...
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Multi-atlas based neonatal brain extraction using atlas library clustering and local label fusion
Brain extraction is one of the most important preprocessing steps in cerebral magnetic resonance (MR) image analysis. Brain extraction from neonatal...
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Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification
Autism spectrum disorder (ASD) is a prevalent psychiatric condition characterized by atypical cognitive, emotional, and social patterns. Timely and...
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Learning Tumor-Induced Deformations to Improve Tumor-Bearing Brain MR Segmentation
We propose a novel framework that applies atlas-based whole-brain segmentation methods to tumor-bearing MR images. Given a patient brain MR image...
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Atlas-Powered Deep Learning (ADL) - Application to Diffusion Weighted MRI
Deep learning has a great potential for estimating biomarkers in diffusion weighted magnetic resonance imaging (dMRI). Atlases, on the other hand,...