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Computational neuroimaging involves analyzing brain images or signals to provide mechanistic insights and predictive tools for human cognition and behavior.
Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Federated learning for privacy preservation in smart healthcare systems: A comprehensive survey
Mansoor Ali, Faisal Naeem, Muhammad Tariq, and Georges Kaddoum · 2022
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Diffusion visual counterfactual explanations
Maximilian Augustin, Valentyn Boreiko, Francesco Croce, and Matthias Hein · 2022
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Deep learning in neuroimaging data analysis: applications, challenges, and solutions
Lev Kiar Avberšek and Grega Repovš · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2022
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Fast unsupervised brain anomaly detection and segmentation with diffusion models
Walter HL Pinaya, Mark S Graham, Robert Gray, Pedro F Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H Mah, Andrew D MacKinnon, James T Teo, Rolf Jager, et al · 2022
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Brain imaging generation with latent diffusion models
Walter HL Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon, Pedro F Da Costa, Virginia Fernandez, Parashkev Nachev, Sebastien Ourselin, and M Jorge Cardoso · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Solving inverse problems in medical imaging with score-based generative models
Yang Song, Liyue Shen, Lei Xing, and Stefano Ermon · 2022
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Dual diffusion implicit bridges for image-to-image translation
Xuan Su, Jiaming Song, Chenlin Meng, and Stefano Ermon · 2022
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Self-supervised learning of brain dynamics from broad neuroimaging data
Armin Thomas, Christopher Ré, and Russell Poldrack · 2022
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Synthetic sleep eeg signal generation using latent diffusion models
Bruno Aristimunha, Raphael Yokoingawa de Camargo, Sylvain Chevallier, Oeslle Lucena, Adam G Thomas, M Jorge Cardoso, Walter Hugo Lopez Pinaya, and Jessica Dafflon · 2023
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Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding
Zijiao Chen, Jiaxin Qing, Tiange Xiang, Wan Lin Yue, and Juan Helen Zhou · 2023
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Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction
Zeyu Han, Yuhan Wang, Luping Zhou, Peng Wang, Binyu Yan, Jiliu Zhou, Yan Wang, and Dinggang Shen · 2023
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Cola-diff: Conditional latent diffusion model for multi-modal mri synthesis
Lan Jiang, Ye Mao, Xiangfeng Wang, Xi Chen, and Chao Li · 2023
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Disc-diff: Disentangled conditional diffusion model for multi-contrast mri super-resolution
Ye Mao, Lan Jiang, Xi Chen, and Chao Li · 2023
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Adaptive latent diffusion model for 3d medical image to image translation: Multi-modal magnetic resonance imaging study
Jonghun Kim and Hyunjin Park · 2024
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Feddiff: Diffusion model driven federated learning for multi-modal and multi-clients
Daixun Li, Weiying Xie, Zixuan Wang, Yibing Lu, Yunsong Li, and Leyuan Fang · 2024
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Rethinking diffusion model for multi-contrast mri super-resolution
Guangyuan Li, Chen Rao, Juncheng Mo, Zhanjie Zhang, Wei Xing, and Lei Zhao · 2024
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Corrdiff: Corrective diffusion model for accurate mri brain tumor segmentation
Wenqing Li, Wenhui Huang, and Yuanjie Zheng · 2024
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Reverse the auditory processing pathway: Coarse-to-fine audio reconstruction from fmri
Che Liu, Changde Du, Xiaoyu Chen, and Huiguang He · 2024
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Generating realistic brain mris via a conditional diffusion probabilistic model
Wei Peng, Ehsan Adeli, Tomas Bosschieter, Sang Hyun Park, Qingyu Zhao, and Kilian M Pohl · 2023
Cited alongside, same era.
High-resolution image reconstruction with latent diffusion models from human brain activity
Yu Takagi and Shinji Nishimoto · 2023
Cited alongside, same era.
Wkgm: weighted k-space generative model for parallel imaging reconstruction
Zongjiang Tu, Die Liu, Xiaoqing Wang, Chen Jiang, Pengwen Zhu, Minghui Zhang, Shanshan Wang, Dong Liang, and Qiegen Liu · 2023
Cited alongside, same era.
Inversesr: 3d brain mri super-resolution using a latent diffusion model
Jueqi Wang, Jacob Levman, Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, M Jorge Cardoso, and Razvan Marinescu · 2023
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Diffusion model as representation learner
Xingyi Yang and Xinchao Wang · 2023
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On the opportunity of causal deep generative models: A survey and future directions
Guanglin Zhou, Lina Yao, Xiwei Xu, Chen Wang, Liming Zhu, and Kun Zhang · 2023
Cited alongside, same era.
Brain diffusion for visual exploration: Cortical discovery using large scale generative models
Andrew Luo, Maggie Henderson, Leila Wehbe, and Michael Tarr · 2024
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Target-guided diffusion models for unpaired cross-modality medical image translation
Yimin Luo, Qinyu Yang, Ziyi Liu, Zenglin Shi, Weimin Huang, Guoyan Zheng, and Jun Cheng · 2024
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Segment anything in medical images
Jun Ma, Yuting He, Feifei Li, Lin Han, Chenyu You, and Bo Wang · 2024
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Multi-modal modality-masked diffusion network for brain mri synthesis with random modality missing
Xiangxi Meng, Kaicong Sun, Jun Xu, Xuming He, and Dinggang Shen · 2024
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Medsegdiff: Medical image segmentation with diffusion probabilistic model
Junde Wu, Rao Fu, Huihui Fang, Yu Zhang, Yehui Yang, Haoyi Xiong, Huiying Liu, and Yanwu Xu · 2024
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Diffusion-ts: Interpretable diffusion for general time series generation
Xinyu Yuan and Yan Qiao · 2024
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Spatio-temporal adaptive diffusion models for eeg super-resolution in epilepsy diagnosis
Tong Zhou and Shuqiang Wang · 2024
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Brainnetdiff: Generative ai empowers brain network construction via multimodal diffusion
Yongcheng Zong, Changhong Jing, Jonathan H Chan, and Shuqiang Wang · 2024
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A new brain network construction paradigm for brain disorder via diffusion-based graph contrastive learning
Yongcheng Zong, Qiankun Zuo, Michael Kwok-Po Ng, Baiying Lei, and Shuqiang Wang · 2024
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Diffusion transformer-augmented fmri functional connectivity for enhanced autism spectrum disorder diagnosis
Haokai Zhao, Haowei Lou, Lina Yao, and Yu Zhang · 2025
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