Machine learning in clinical neuroimaging 6th international workshop, MLCN 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, proceedings /
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-le...
| Corporate Authors: | MLCN (Workshop) Vancouver, B.C.) |
|---|---|
| Other Authors: | MLCN (Workshop), Abdulkadir, Ahmed,, Bathula, Deepti R.,, Dvornek, Nicha C.,, Govindarajan, Sindhuja T.,, Habes, Mohamad,, Kumar, Vinod,, Leonardsen, Esten,, Wolfers, Thomas,, Xiao, Yiming,, SpringerLink (Online service), International Conference on Medical Image Computing and Computer-Assisted Intervention |
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
[2023]
|
| Physical Description: |
1 online resource (x, 174 pages) : illustrations (chiefly color). |
| Series: |
Lecture notes in computer science ;
14312. |
| Subjects: |
Table of Contents:
- 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.