These papers are made available for personal use only, subject to author's and publisher's copyright.
Journal Publications
Liang Sun, Wei Shao, Daoqiang Zhang, Mingxia Liu. Anatomical Attention Guided Deep Networks for ROI Segmentation of Brain MR Images. IEEE Transactions on Medical Imaging, 2019. [download]
Jiashuang Huang, Qi Zhu, Mingliang Wang, Luping Zhou, Zhiqiang Zhang, Daoqiang Zhang. Coherent Pattern in Multi-layer Brain Networks: Application to Epilepsy Identification. IEEE Journal of Biomedical and Health Informatics, 2019. [download]
Mingliang Wang, Chunfeng Lian, Dongren Yao, Daoqiang Zhang, Mingxia Liu, Dinggang Shen. Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network. IEEE Transactions on Biomedical Engineering, 2019. [download]
Liang Sun, Wei Shao, Mingliang Wang, Daoqiang Zhang, Mingxia Liu. High-order Feature Learning for Multi-atlas based Label Fusion: Application to Brain Segmentation with MRI. IEEE Transactions on Image Processing, 2019. [download]
Meiling Wang, Wei Shao, Xiaoke Hao, Li Shen, Daoqiang Zhang. Identify Consistent Cross-Modality Imaging Genetic Patterns via Discriminant Sparse Canonical Correlation Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019. [download]
Liang Sun, Daoqiang Zhang, Chunfeng Lian, Li Wang, Zhengwang Wu, Wei Shao, Weili Lin, Dinggang Shen, Gang Li, UNC/UMN Baby Connectome Project Consortium. Topological correction of infant white matter surfaces using anatomically constrained convolutional neural network. NeuroImage, 2019, 198: 114-124. [download]
Qi Zhu, Ning Yuan, Jiashuang Huang, Xiaoke Hao, Daoqiang Zhang. Multi-modal AD classification via self-paced latent correlation analysis. Neurocomputing, 2019, 355: 143-154. [download]
Chen Zu, Yue Gao, Brent Munsell, Minjeong Kim, Ziwen Peng, Jessica R Cohen, Daoqiang Zhang, Guorong Wu. Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning. Brain imaging and behavior, 2019, 13(4): 879-892. [download]
Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu. Identifying autism spectrum disorder with multi-site fMRI via low-rank domain adaptation. IEEE Transactions on Medical Imaging, 2019. [download]
Wei Shao, Zhi Han, Jun Cheng, Liang Cheng, Tongxin Wang, Liang Sun, Zixiao Lu, Jie Zhang, Daoqiang Zhang, Kun Huang. Integrative analysis of pathological images and multi-dimensional genomic data for early-stage cancer prognosis. IEEE transactions on medical imaging, 2019, 39(1): 99-110. [download]
Liang Sun, Li Zhang, Daoqiang Zhang. Multi-Atlas Based Methods in Brain MR Image Segmentation. Chinese Medical Sciences Journal 34.2 (2019): 110-119. [download]
Meiling Wang, Xiaoke Hao, Jiashuang Huang, Wei Shao, Daoqiang Zhang. Discovering network phenotype between genetic risk factors and disease status via diagnosis-aligned multi-modality regression method in Alzheimer's disease. Bioinformatics, 2019, 35(11): 1948-1957. [download]
Liang Sun, Chen Zu, Wei Shao, Junye Guang, Daoqiang Zhang, Mingxia Liu. Reliability-based robust multi-atlas label fusion for brain MRI segmentation. Artificial intelligence in medicine, 2019, 96: 12-24. [download]
Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Li Shen, Xijia Xu, Daoqiang Zhang, Mingxia Liu. Hierarchical Structured Sparse Learning for Schizophrenia Identification. Neuroinformatics, 2019: 1-15. [download]
Muhammad Yousefnezhad, Daoqiang Zhang. Multi-Objective Cognitive Model: a Supervised Approach for Multi-subject fMRI Analysis. Neuroinformatics, 2019, 17(2): 197-210. [download]
Mingliang Wang, Daoqiang Zhang, Dinggang Shen, Mingxia Liu. Multi-task exclusive relationship learning for Alzheimer's disease progression prediction with longitudinal data. Medical image analysis, 2019, 53: 111-122. [download]
Bo Cheng, Mingxia Liu, Daoqiang Zhang, Dinggang Shen, Alzheimer's Disease Neuroimaging Initiative. Robust multi-label transfer feature learning for early diagnosis of Alzheimer's disease. Brain imaging and behavior, 2019, 13(1): 138-153. [download]
Wei Shao, Sheng-Jun Huang, MingXia Liu, Daoqiang Zhang. Querying Representative and Informative Super-pixels for Filament Segmentation in Bioimages. IEEE/ACM transactions on computational biology and bioinformatics, 2019. [download]
Conference Publications
Muhammad Yousefnezhad, Daoqiang Zhang*. Deep Hyperalignment. In: 31st Conference on Neural Information Processing Systems (NIPS'17), Long Beach, CA, 2017. [download]
Muhammad Yousefnezhad, Daoqiang Zhang*. Local Discriminant Hyperalignment for multi-subject fMRI data alignment. In: 2017 AAAI Conference on Artificial Intelligence (AAAI'17), San Francisco, CA, 2017. [download]
Yi Ding, Shengjun Huang, Daoqiang Zhang*. Margin Distribution Logistic Machine. In: 2017 SIAM International Conference on Data Mining (SDM'17), Houston, Texas, 2017. [download]
Muhammad Yousefnezhad, Daoqiang Zhang*. Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains. In: 2017 SIAM International Conference on Data Mining (SDM'17), Houston, Texas, 2017. [download]
Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Xijia Xu, Daoqiang Zhang*. Multi-level Multi-task Structured Sparse Learning for Diagnosis of Schizophrenia Disease. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'17), Quebec City, Canada, 2017. [download]
Liang Sun, Wei Shao, Daoqiang Zhang*. High-order Boltzmann machine-based unsupervised feature learning for multi-atlas segmentation. In: IEEE International Symposium on Biomedical Imaging (ISBI'17), Melbourne, Australia, 2017. [download]
