2022
Xiyue Wang, Sen Yang, Jun Zhang, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang, Xiao Han.Transformer-based unsupervised contrastive learning for histopathological image classification. Medical Image Analysis. 2022.
Wenhua Zhang*, Jun Zhang*, Sen Yang, Xiyue Wang, Wei Yang, Junzhou Huang, Wenping Wang, Xiao Han. Knowledge-Based Representation Learning for Nucleus Instance Classification from Histopathological Images. IEEE Transactions on Medical Imaging. 2022 (*Co-first Author)
Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Mingxuan Gao, Junzhou Huang, Jianhua Yao. Multi-level attention graph neural network based on co-expression gene modules for disease diagnosis and prognosis. Bioinformatics. 2022;38:2178-2186
Donglin Di, Jun Zhang, Fuqiang Lei, Qi Tian, Yue Gao. Big-Hypergraph Factorization Neural Network for Survival Prediction From Whole Slide ImageIEEE Transactions on Image Processing 2022; 31:1149-1160
Xiyue Wang, Ruijie Wang, Sen Yang, Jun Zhang, Minghui Wang, Dexing Zhong, Jing Zhang, Xiao Han. Combining Radiology and Pathology for Automatic Glioma Classification. Frontiers in Bioengineering and Biotechnology. 2022; 10: 841958
2021
Jun Zhang*, Zhiyuan Hua*, Kezhou Yan, Kuan Tian, Jianhua Yao, Eryun Liu, Mingxia Liu, and Xiao Han. Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images. Medical image analysis 73 (2021): 102183. (*Co-first Author)
Jun Zhang, Mingxia Liu, Ke Lu, Yue Gao. Group-Wise Learning for Aurora Image Classification with Multiple Representations. IEEE Transactions on Cybernetics, 51 (8), 4112 – 4124, 2021.
Meng Yue*, Jun Zhang*, Xinran Wang, Kezhou Yan, Lijing Cai, Kuan Tian, Shuyao Niu et al. “Can AI-assisted microscope facilitate breast HER2 interpretation? A multi-institutional ring study.” Virchows Archiv (2021): 1-7.(*Co-first Author)
Lijing Cai, Kezhou Yan, Hong Bu, Meng Yue, Pei Dong, Xinran Wang, Lina Li, Kuan Tian, Haochen Shen, Jun Zhang, Junzhou Huang, Xiao Han, Jianhua Yao, Yueping Liu. Improving Ki67 Assessment Concordance with AI‐Empowered Microscope: A Multi‐institutional Ring Study. Histopathology (2021).
2020
Jun Zhang, Kuan Tian, Pei Dong, Haocheng Shen, Kezhou Yan, Jianhua Yao, Junzhou Huang, Xiao Han. Microscope Based HER2 Scoring System. arXiv preprint arXiv:2009.06816, 2020.
Jun Zhang*, Mingxia Liu*, Li Wang, Si Chen, et al. Context-Guided Fully Convolutional Networks for Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization. Medical Image Analysis, 60:101621, 2020. (*Co-first Author)
Chunfeng Lian, Mingxia Liu, Jun Zhang, Dinggang Shen. Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer’s Disease Diagnosis using Structural MRI. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(4):880-893, 2020.
Rongbo Shen, Ke Zhou, Kezhou Yan, Kuan Tian, Jun Zhang. Multicontext multitask learning networks for mass detection in mammogram. Medical Physics,47(4):1566-1578, 2020.
Eryun Liu, Kangping Chen, Zhiyu Xiang, Jun Zhang. Conductive particle detection via deep learning for ACF bonding in TFT-LCD manufacturing. Journal of Intelligent Manufacturing,31:1037-1049, 2020.
2019
Jun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski. Hierarchical convolutional neural networks for segmentation of breast tumors in MRI with application to radiogenomics. IEEE Transactions on Medical Imaging, 38(2): 435-447, 2019.
Mingxia Liu*, Jun Zhang*, Chunfeng Lian, Dinggang Shen. “Weakly-Supervised Deep Learning for Brain Disease Prognosis using MRI and Incomplete Clinical Scores”. IEEE Transactions on Cybernetics, 50 (7), 3381-3392, 2019. (*Co-first Author, Accepted)
Mingxia Liu*, Jun Zhang*, Ehsan Adeli, Dinggang Shen. Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer’s Disease Diagnosis, IEEE Transactions on Biomedical Engineering, 66 (5): 1195-1206, 2019. (*Co-first Author)
Liang Wang, Haochen Shen, Jun Zhang, Yanchun Zhu, Cheng Jiang. A Clifford Analytic Signal-Based Breast Lesion Segmentation Method for 4D Spatial-Temporal DCE-MRI Sequences. IEEE Access,8:3901-3910, 2019.
Z Zhu, E Albadawy, A Saha, Jun Zhang, MR Harowicz, MA Mazurowski. Deep Learning for Identifying Radiogenomic Associations in Breast Cancer, Computers in biology and medicine, 109:85-90,2019.
Z Zhu, M Harowicz, Jun Zhang, A Saha, LJ Grimm, ES Hwang. Deep Learning Analysis of Breast MRIs for Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ, Computers in biology and medicine, 115:103498,2019.
2018
Jun Zhang, Ashirbani Saha, Brian J. Soher, Maciej A. Mazurowski, Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images, arXiv preprint arXiv:1807.02152, 2018.
Chuang Niu, Jun Zhang, Qian Wang, Jimin Liang. Weakly Supervised Learning for Joint Key Local Structure Localization and Classification of Aurora Image, IEEE Transactions on Geoscience and Remote Sensing, 56 (12):7133-7146 2018.
Mingxia Liu*, Jun Zhang*, Dong Nie, Pew-Thian Yap, Dinggang Shen. Anatomical Landmark based Deep Feature Representation for MR Images in Brain Disease Diagnosis, IEEE Journal of Biomedical and Health Informatics, 22(5): 1476-1485, 2018. (*Co-first Author)
Mingxia Liu*, Jun Zhang*, Ehsan Adeli, Dinggang Shen. Landmark-based Deep Multi-Instance Learning for Brain Disease Diagnosis. Medical Image Analysis, 43: 157-168, 2018.(*Co-first Author)
Liang Cao, Long Li, Jifeng Zheng, Xin Fan, Feng Yin, Hui Shen, Jun Zhang#. Multi-task Neural Networks for Joint Hippocampus Segmentation and Clinical Score Regression. Multimedia Tools and Applications, 1-18, 2018. (#Correspoinding Author)
Chunfeng Lian*, Jun Zhang*, Mingxia Liu, Xiaoping Zong, Weili Lin, Dinggang Shen. Multi-Channel Multi-Scale Fully Convolutional Network for 3D Perivascular Spaces Segmentation in 7T MR Images. Medical Image Analysis, 46: 106-117, 2018. (*Co-first Author)
Xiaohuan Cao, Jianhua Yang, Jun Zhang, Qian Wang, Pew-Thian Yap, Dinggang Shen. Deformable Image Registration Using Cue-aware Deep Regression Network. IEEE Transaction on Biomedical Engineering, 65(9):1900-1911. (Covered Article)
2017
Jun Zhang*, Mingxia Liu*, Dinggang Shen. Detecting Anatomical Landmarks from Limited Medical Imaging Data using Two-Stage Task-Oriented Deep Neural Networks. IEEE Trans. on Image Processing, 26(10): 4753-4764, 2017. (*Co-first Author)
Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen. Alzheimer’s Disease Diagnosis using Landmark-based Features from Longitudinal Structural MR Images. IEEE Journal of Biomedical and Health Informatics, 21(3): 1607-1616, 2017
Jun Zhang, Yaozong Gao, Sang Hyun Park, Xiaopeng Zong, Weili Lin, Dinggang Shen. “Structured Learning for 3D Perivascular Spaces Segmentation Using Vascular Features.” IEEE Trans. on Biomedical Engineering, 64(12): 2803-2812, 2017. (Featured Article)
Jun Zhang, Qian Wang, Zejun Hu, Mingxia Liu. Auroral Event Representation based on the N-ary Fusion of Multiple Oriented Energies. Neurocomputing 253: 42-48, 2017.
Jun Zhang, Jimin Liang, Haihong Hu. Multi-view texture classification using hierarchical synthetic images. Multimedia Tools and Applications 76(16), 17511-17523, 2017
Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen. View-Aligned Hypergraph Learning for Alzheimer’s Disease Diagnosis with Incomplete Multi-modality Data. Medical Image Analysis, 36(2): 123-134, 2017.
Zhenzhen, Xu, Bo Tao, Yu Li, Jun Zhang, Xiaochao Qu, Feng Cao, Jimin Liang. 3D Fusion Framework for Infarction and Angiogenesis Analysis in a Myocardial Infarct Minipig Model. Molecular Imaging 16: 1536012117708735, 2017.
Yingkun Hou, Sang Hyun Park, Qian Wang, Jun Zhang, Xiaopeng Zong, Weili Lin, and Dinggang Shen. Enhancement of Perivascular Spaces in 7T MR Image using Haar Transform of Non-local Cubes and Block-matching Filtering. Scientific Reports 7, 2017.
Le An, Ehsan Adeli, Mingxia Liu, Jun Zhang, Seong-Whan Lee, Dinggang Shen. A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis. Scientific Reports 7, 2017.
Liu, Mingxia, Jun Zhang#, Xiaochun Guo, and Liujuan Cao. Hypergraph Regularized Sparse Feature Learning. Neurocomputing. 237: 185-192, 2017. (#Correspoinding Author)
2016
Jun Zhang, Yue Gao, Yaozong Gao, Munsell Brent, and Dinggang Shen. Detecting Anatomical Landmarks for Fast Alzheimer’s Disease Diagnosis. IEEE Trans. on Medical Imaging, 35(12): 2524-2533, 2016.
Jun Zhang, Yaozong Gao, Li Wang, Zhen Tang, James J. Xia, and Dinggang Shen. Automatic Craniomaxillofacial Landmark Digitization via Segmentation-guided Partially-joint Regression Forest Model and Multi-scale Statistical Features. IEEE Trans. on Biomedical Engineering, 63(9): 1820-1829, 2016.
2015
Jun Zhang, Jimin Liang, Chunhui Zhang, and Heng Zhao. Scale Invariant Texture Representation based on Frequency Decomposition and Gradient Orientation. Pattern Recognition Letters, 51: 57-62, 2015.
Chunhui Zhang, Jimin Liang, Jun Zhang, and Heng Zhao. A New Shape Prior Model with Rotation Invariance. Pattern Recognition Letters, 54: 82-88, 2015.
2014
Jun Zhang, Duofang Chen, Jimin Liang, Huadan Xue, Jing Lei, Qin Wang, Dongmei Chen, Ming Meng, Zhengyu Jin, and Jie Tian. Incorporating MRI Structural Information into Bioluminescence Tomography: System, Heterogeneous Reconstruction and In Vivo Quantification. Biomedical Optics Express, 5(6): 1861, 2014.
Chunhui Zhang, Jun Zhang, Heng Zhao, and Jimin Liang. A Part-based Probabilistic Model for Object Detection with Occlusion. PloS One, 9(1): e84624, 2014.
2013
Jun Zhang, Jimin Liang, and Heng Zhao. Local Energy Pattern for Texture Classification using Self-adaptive Quantization Thresholds. IEEE Trans. on Image Processing, 22(1): 31-42, 2013.
Jun Zhang, Heng Zhao, and Jimin Liang. Continuous Rotation Invariant Local Descriptors for Texton Dictionary-based Texture Classification. Computer Vision and Image Understanding, 117(1): 56-75, 2013.
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