News – MAGIC Lab

2024

[03/09/2024] Hao’s review paper on federated learning for medical image analysis has been accepted by the journal Pattern Recognition.聽Congratulations!
[03/07/2024] Yuqi’s survey paper on source-free unsupervised domain adaptation has been accepted by the journal Neural Networks.聽Congratulations!
[03/05/2024] Lintao’s work on hybrid MRI representation learning for cognitive trajectory analysis of late-life depression has been accepted by the journal Medical Image Analysis. Congratulations!
[02/22/2024] Qianqian’s work on brain modularity-based fMRI analysis has been accepted by IEEE Transactions on Biomedical Engineering. Congratulations!
[01/21/2024] Congratulations to Lintao and Minhui on getting their work accepted at OHBM 2024!

2023

[10/08/2023] Congratulations to Mengqi on receiving the Best Paper Award at the 14th International Workshop on Machine Learning in Medical Imaging (held in conjunction with MICCAI 2023)!
[08/05/2023] Our work on self-supervised cerebellum segmentation has been accepted by Nature Communications. Congratulations!
[07/19/2023] Dr. Liu received the Outstanding Area Chair Award from The 26^th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). Congratulations!
[06/24/2023] Lintao’s paper and Qianqian’s paper have been accepted by MICCAI 2023. Congratulations!
[05/03/2023] Yuqi’s work on collaborative learning for fMRI harmonization has been accepted by Human Brain Mapping. Congratulations!
[03/04/2023] Our work on MRI-based progression prediction of subjective cognitive decline has been accepted by IEEE Journal of Biomedical and Health Informatics. Congratulations!
[01/03/2023] Hao’s paper on domain adaptation toolbox for medical data analysis has been accepted by the journal NeuroImage. Congratulations!

2022

[11/25/2022] Yuqi’s work on unsupervised functional MRI harmonization has been accepted by the journal Medical Image Analysis. Congratulations!
[10/26/2022] Our work on resting-state fMRI adaptation was selected as Feature Paper by the journal Brain Sciences.
[09/18/2022] Dr. Hao Guan received the Best Paper Award for our work on spectrum-based MRI harmonization at the 13th International Workshop on Machine Learning in Medical Imaging. Congratulations!
[09/17/2022] Our article on estimating brain functional connectivity network via correlation-preserving embedding has been selected as the Highlight Paper by the journal Medical & Biological Engineering & Computing.
[09/15/2022] Our open-source software, Domain Adaptation Toolbox聽for Medical聽data analysis聽(DomainATM), has been released, designed for fast facilitation and easy customization of cross-domain data adaptation and harmonization methods for biomedical data analysis.

[08/18/2022] Our work on consistent connectome landscape mining for cross-site brain disease analysis with resting-state fMRI has been accepted by the journal Medical Image Analysis.

[08/18/2022] One paper on resting-state functional connectivity analysis investigating the association of lifetime concussion history and repetitive head impact exposure in former collegiate American football players has been accepted by the journal PLOS ONE.

[08/01/2022] Four papers have been accepted by MLMI 2022.

[06/02/2022] Minhui’s paper on structural MRI adaptation for clinical progression prediction of subjective cognitive decline has been accepted by MICCAI 2022. Congratulations!

[04/06/2022] One paper on functional and structural MRI fusion for brain disorder analysis has been accepted by the journal of Frontiers In Neuroinformatics. Congratulations!

[03/16/2022] Yuqi’s abstract on unsupervised functional MRI adaptation has been accepted by the 2022 OHBM Annual Meeting. Congratulations!

2021

[10/18/2021] One paper on multi-site functional MRI harmonization has been accepted by the journal of Medical Image Analysis. Congratulations!
[10/07/2021] Our work on multi-modality neuroimage fusion for conversion prediction of subjective cognitive decline has been accepted by the journal of Medical Image Analysis. Congratulations!
[09/24/2021] Our review paper on domain adaptation for medical image analysis has been accepted by the journal IEEE Transactions on Biomedical Engineering. Congratulations!
[08/08/2021] Three papers have been accepted by MLMI 2021.
[07/24/2021] Two papers have been accepted by PRIME 2021.
[06/24/2021] Dongren Yao has won the Travel Grant awarded by MICCAI 2021.
[06/15/2021] Our work on neuroimage synthesis has been accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence. Congratulations!
[05/13/2021] Two papers have been Early Accepted by MICCAI 2021 (early acceptance rate: 13%).
[04/03/2021] One paper on multi-site MRI harmonization for automated prognosis of neurodegenerative brain disorders has been accepted by Medical Image Analysis.
[03/29/2021] Our work on modeling dynamic patterns of brain functional connectivity networks has been accepted by Medical Image Analysis.
[03/15/2021] Two abstracts have been accepted by the 2021 OHBM Annual Meeting.
[01/26/2021] One paper on multi-task learning for clinical score regression has been accepted by IEEE Transactions on Neural Networks and Learning Systems.
[01/25/2021] Our work on hypergraph learning-based multimodal data fusion methods for AD diagnosis has been accepted by Frontiers in Neuroscience.
[01/18/2021] One paper on evaluating the robustness of deep diagnostic models by adversarial attacks has been accepted by Medical Image Analysis.
[01/08/2021] Two papers on major depressive disorder analysis and mild cognitive impairment progress prediction have been accepted by IEEE International Symposium on Biomedical Imaging (ISBI 2021).
[01/01/2021] Our work on graph learning-based structural and functional connectivity analysis for brain disorder diagnosis has been accepted by IEEE Transactions on Medical Imaging.

2020

[10/09/2020] Li Zhang’s survey paper on deep learning for neuroimaging-based brain disorder analysis has been accepted by Frontiers in Neuroscience. Congratulations!
[10/06/2020] Yunbi Liu has received the Travel Award from MICCAI 2020.聽Congratulations!
[10/05/2020] Erkun Yang’s paper on brain image retrieval has been accepted聽by IEEE聽Transactions on Medical Imaging.聽Congratulations!
[10/04/2020] We are organizing the 11th International Workshop on Machine Learning in Medical Intelligence (MLMI) in conjunction with MICCAI 2020, and it has been held successfully as a fully virtual workshop in Lima, Peru. The proceeding can be found here. [ link]
[09/15/2020] Shuai Wang’s paper on organ segmentation in prostate cancer radiotherapy has been accepted by IEEE Transactions on Medical Imaging. Congratulations!
[08/02/2020] Four papers have been accepted by the International Workshop on Machine Learning in Medical Imaging (MLMI 2020) and the International Workshop on Domain Adaptation and Representation Transfer (DART 2020).聽
[06/23/2020] Three papers have been accepted聽by聽MICCAI 2020 (main conference).聽
[06/19/2020] Chunfeng Lian’s paper on hybrid network for AD diagnosis has been accepted by IEEE Transactions on Cybernetics.聽Congratulations!
[03/17/2020] Yongsheng Pan’s paper on brain disease identification using incomplete multimodality data has been accepted by IEEE Transactions on Medical Imaging.聽Congratulations!

2019

[12/19/2019] Tao聽Zhou‘s paper on multimodal latent feature learning for early dementia diagnosis has been聽accepted by聽Medical Image Analysis.聽Congratulations!
[11/10/2019] Weida Li’s paper on graph-kernel-based functional alignment of fMRI data has been accepted by AAAI 2020聽(Acceptance Rate: 20.6%). Congratulations!
[11/02/2019] Liang Sun鈥檚 paper on brain MRI segmentation has been accepted by IEEE Transactions on Image Processing. Congratulations!
[10/17/2019] Dongren Yao’s paper on multi-scale graph learning for brain fMRI data analysis has won the Best Paper Award in GLMI 2019. Congratulations!
[08/13/2019] Yongsheng Pan’s paper on analysis of adolescent brain cognitive development has been accepted by GLMI 2019. Congratulations!
[08/ 13/2019] Dongren Yao’s paper on multi-template fMRI analysis for ASD/ADHD identification using triplet graph convolutional network has been accepted by GLMI 2019聽as聽Oral Presentation. Congratulations!
[08/13/2019] Jing Zhang’s paper on unsupervised conditional consensus adversarial learning for domain adaptation has been accepted by MLMI 2019. Congratulations!
[07/26/2019] Mingliang Wang鈥檚 paper on fMRI-based identification of autism from multi-centers has been accepted by IEEE Transactions on Medical Imaging. Congratulations!
[07/16/2019] Mingliang Wang has won the Best Poster Award in Medical Image Computing Seminar (MICS).聽Congratulations!
[07/06/2019] Four papers have been accepted by MICCAI 2019 (main conference).
[04/18/2019] Tao Zhou鈥檚 paper on latent聽representation聽learning聽for聽incomplete聽data聽based AD聽diagnosis聽has been accepted by聽IEEE Transactions on Medical Imaging. 聽Congratulations!
[03/20/2019] We are organizing the 10th International Workshop on Machine Learning in Medical Imaging聽(MLMI), held together with MICCAI 2019, in Shenzhen, China. The proceedings could be found here. [ link]
[03/20/2019] We are organizing the 1st International Workshop on Graph Learning in Medical Imaging聽(GLMI), held together with MICCAI 2019, in Shenzhen, China. The proceedings could be found here. [ link]
[03/18/2019] Yongsheng Pan has won the Best Performance Award (#1聽 Ranked) in an ISBI Challenge聽on cell classification. Congratulations!
[03/17/2019] Mingxia Liu’s paper on the development of weakly-supervised deep learning for brain disease prognosis (based on incomplete data) has been accepted by IEEE Transactions on Cybernetics. Congratulations!
[01/28/2019] Mingliang Wang’s paper on multi-task AD longitudinal prediction has been accepted by Medical Image Analysis. Congratulations!

2018

[12/11/2018] Chunfeng Lian’s paper on the development of novel hierarchical FCN for simultaneous atrophy location and AD diagnosis has been accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence. Congratulations!
[11/01/2018] Mingliang Wang’s paper on fMRI-based discriminative hub detection for brain disease identification has been accepted by AAAI 2019. Congratulations!
[09/10/2018] Mingxia Liu’s paper on deep learning based joint AD classification and prediction has been accepted by IEEE Transactions on Biomedical Engineering. Congratulations!
[03/31/2018] Tao聽Zhou‘s paper on brain-wide genome-wide association study for Alzheimer’s disease diagnosis has been accepted by IEEE Transactions on Biomedical Engineering.聽Congratulations!
[03/20/2018] We are organizing the 9th聽International Workshop on Machine Learning in Medical Imaging聽(MLMI), held together with MICCAI 2018, in Granada, Spain. The proceedings could be found here. [ link]