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ORCIDMLCN@MICCAI 2023: Vancouver, BC, Canada
- Ahmed Abdulkadir
, Deepti R. Bathula, Nicha C. Dvornek, Sindhuja Tirumalai Govindarajan, Mohamad Habes, Vinod Kumar, Esten H. Leonardsen, Thomas Wolfers, Yiming Xiao:
Machine Learning in Clinical Neuroimaging - 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings. Lecture Notes in Computer Science 14312, Springer 2023, ISBN 978-3-031-44857-7
Machine Learning
- Michael Tran Duong, Sandhitsu R. Das, Pulkit Khandelwal, Xueying Lyu, Long Xie, Paul A. Yushkevich, David A. Wolk, Ilya M. Nasrallah:
Image-to-Image Translation Between Tau Pathology and Neuronal Metabolism PET in Alzheimer Disease with Multi-domain Contrastive Learning. 3-13 - Reagan Dugan, Owen T. Carmichael:
Multi-shell dMRI Estimation from Single-Shell Data via Deep Learning. 14-22 - Qi Wang, Lucas Mahler, Julius Steiglechner, Florian Birk, Klaus Scheffler, Gabriele Lohmann:
A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging. 23-33 - Zhuotong Cai, Tianyi Zeng, Eléonore V. Lieffrig, Jiazhen Zhang, Fuyao Chen, Takuya Toyonaga, Chenyu You, Jingmin Xin, Nanning Zheng, Yihuan Lu, James S. Duncan, John A. Onofrey:
Cross-Attention for Improved Motion Correction in Brain PET. 34-45 - Mumu Aktar, Hassan Rivaz, Marta Kersten-Oertel, Yiming Xiao:
VesselShot: Few-shot Learning for Cerebral Blood Vessel Segmentation. 46-55 - Zhenghan Fang, Hyeong-Geol Shin, Peter C. M. van Zijl, Xu Li, Jeremias Sulam:
WaveSep: A Flexible Wavelet-Based Approach for Source Separation in Susceptibility Imaging. 56-66 - Kai-Cheng Chuang, Sreekrishna Ramakrishnapillai, Krystal Kirby, Arend W. A. Van Gemmert, Lydia Bazzano, Owen T. Carmichael:
Joint Estimation of Neural Events and Hemodynamic Response Functions from Task fMRI via Convolutional Neural Networks. 67-78 - Jiyao Wang, Nicha C. Dvornek, Lawrence H. Staib, James S. Duncan:
Learning Sequential Information in Task-Based fMRI for Synthetic Data Augmentation. 79-88
Clinical Applications
- Elizabeth Haddad, Myrl G. Marmarelis, Talia M. Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad:
Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain. 91-101 - Corentin Ambroise, Vincent Frouin, Benoit Dufumier, Edouard Duchesnay, Antoine Grigis:
MixUp Brain-Cortical Augmentations in Self-supervised Learning. 102-111 - Artur Paulo, Fabiano Filho, Tayran Olegário, Bruna Pinto, Rafael Loureiro, Guilherme Ribeiro, Camila Silva, Regiane Carvalho, Paulo Santos, Eduardo Reis, Giovanna Mendes, Joselisa de Paiva, Márcio Reis, Letícia Rittner:
Brain Age Prediction Based on Head Computed Tomography Segmentation. 112-122 - Lucas Mahler, Qi Wang, Julius Steiglechner, Florian Birk, Samuel Heczko, Klaus Scheffler, Gabriele Lohmann:
Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification. 123-132 - Nicha C. Dvornek, Catherine Sullivan, James S. Duncan, Abha R. Gupta:
Copy Number Variation Informs fMRI-Based Prediction of Autism Spectrum Disorder. 133-142 - Anoop Benet Nirmala, Tanweer Rashid, Elyas Fadaee, Nicolas Honnorat, Karl Li, Sokratis Charisis, Di Wang, Aishwarya Vemula, Jinqi Li, Peter Fox, Timothy E. Richardson, Jamie M. Walker, Kevin Bieniek, Sudha Seshadri, Mohamad Habes:
Deep Attention Assisted Multi-resolution Networks for the Segmentation of White Matter Hyperintensities in Postmortem MRI Scans. 143-152 - Adam Marcus, Paul Bentley, Daniel Rueckert:
Stroke Outcome and Evolution Prediction from CT Brain Using a Spatiotemporal Diffusion Autoencoder. 153-162 - Petra Lenzini, Thomas Earnest, Sung Min Ha, Abdalla Bani, Aristeidis Sotiras, Janine Bijsterbosch:
Morphological Versus Functional Network Organization: A Comparison Between Structural Covariance Networks and Probabilistic Functional Modes. 163-172
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