Machine Learning in Clinical Neuroimaging 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings için kapak resmi
Başlık:
Machine Learning in Clinical Neuroimaging 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings
Yazar:
Abdulkadir, Ahmed. editor.
ISBN:
9783031448584
Basım Bilgisi:
1st ed. 2023.
Fiziksel Tanımlama:
X, 174 p. 52 illus., 47 illus. in color. online resource.
Seri:
Lecture Notes in Computer Science, 14312
İçerik:
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.
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