Machine learning in clinical neuroim...
MLCN (Workshop) (2023 :)

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  • Machine learning in clinical neuroimaging = 6th International Workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Machine learning in clinical neuroimaging/ edited by Ahmed Abdulkadir ... [et al.].
    Reminder of title: 6th International Workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023 : proceedings /
    remainder title: MLCN 2023
    other author: Abdulkadir, Ahmed.
    corporate name: MLCN (Workshop)
    Published: Cham :Springer Nature Switzerland : : 2023.,
    Description: x, 174 p. :ill. (chiefly color), digital ;24 cm.
    [NT 15003449]: Machine Learning -- Image-to-Image Translation between Tau Pathology and Neuronal Metabolism PET in Alzheimer Disease with Multi-Domain Contrastive Learning -- Multi-Shell dMRI Estimation from Single-Shell Data via Deep Learning -- A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging -- Cross-Attention for Improved Motion Correction in Brain PET -- VesselShot: Few-shot learning for cerebral blood vessel segmentation -- WaveSep: A Flexible Wavelet-based Approach for Source Separation in Susceptibility Imaging -- Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks -- Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation -- Clinical Applications -- Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain -- MixUp brain-cortical augmentations in self-supervised learning -- Brain age prediction based on head computed tomography segmentation -- Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification -- Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder -- Deep attention assisted multi-resolution networks for the segmentation of white matter hyperintensities in postmortem MRI scans -- Stroke outcome and evolution prediction from CT brain using a spatiotemporal diffusion autoencoder -- Morphological versus Functional Network Organization: A Comparison Between Structural Covariance Networks and Probabilistic Functional Modes.
    Contained By: Springer Nature eBook
    Subject: Diagnostic imaging - Congresses. - Digital techniques -
    Online resource: https://doi.org/10.1007/978-3-031-44858-4
    ISBN: 9783031448584
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