This book constitutes the refereed proceedings of the 6th International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2023, held in Conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023.
The book includes 16 papers which were carefully reviewed and selected from 28 full-length submissions.
The 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023) aims to bring together the top researchers in both machine learning and clinical neuroscience as well as tech-savvy clinicians to address two main challenges: 1) development of methodological approaches for analyzing complex and heterogeneous neuroimaging data (machine learning track); and 2) filling the translational gap in applying existing machine learning methods in clinical practices (clinical neuroimaging track).
The papers are categorzied into topical sub-headings on Machine Learning and Clinical Applications.
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-col=
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