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施俊 博士,教授,博导,副院长 |
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办公室: |
上海大学南陈路333号翔英大楼529室 |
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通信地址(邮政编码): |
上海市上大路99号83信箱(200444) |
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电话: |
021 - 66138178 / 66137269 |
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电子邮件: |
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个人主页: |
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研究方向:(硕士生招生名额:学硕 1 名,专硕 1 名) 机器学习(深度学习)方法、医学图像(超声图像、核磁共振成像等)分析、医学信号(脑电信号、肌电信号等)处理、康复工程 教育经历: 2000.09 –
2005.06,中国科学技术大学,电子工程与信息科学系,博士 1996.09 –
2000.06,中国科学技术大学,电子工程与信息科学系,学士 工作经历: 2005.06 – 至今,上海大学,通信与信息工程学院,讲师,副教授,教授 2011.01 –
2012.01,北卡罗来纳大学教堂山分校,生物医学成像中心,访问学者 2009.07 –
2009.10,香港理工大学,医疗科技与资讯学系,访问学者 2004.07 –
2004.11,香港理工大学,赛马会复康科技中心,研究助理 2002.07 –
2003.04,香港理工大学,赛马会复康科技中心,研究助理 学术活动: MICS委员会轮值主席(2020-2021) 会议主席:2016医学影像信息处理研讨会暨第二届长三角地区医学影像分析论坛 组委会成员:2017第四届医学图像计算青年研讨会 主持项目: 国家自然科学基金面上项目、国家自然科学基金青年基金项目、国家自然科学基金重大科研仪器研制项目(合作单位主持)、国家自然科学基金重点项目(合作单位主持)、上海市自然科学基金面上项目、上海市科委项目、上海市教委项目等。 代表性期刊论文: [1] Jun Shi, Xiao Zheng, Yan Li, Qi Zhang, Shihui Ying. Multimodal neuroimaging feature learning
with multimodal stacked deep polynomial networks for diagnosis of Alzheimer's
disease. IEEE Journal of Biomedical and
Health Informatics. 2018, 22(1): 173-183. (Highly Cited
Paper) [2] Feng Shi#, Jun Wang#,
Jun Shi#, Ziyan Wu, Qian Wang, Zhenyu
Tang, Kelei He, Yinghuan
Shi, Dinggang Shen*. Review of artificial
intelligence techniques in imaging data acquisition, segmentation and
diagnosis for COVID-19. IEEE Reviews in
Biomedical Engineering. 2021, 14: 4-15. (#Equal Contribution, Highly Cited
Paper) [3] Zhongyi Hu, Jun Wang, Chunxiang Zhang, Zhenzhen Luo,
Xiaoqing Luo, Lei Xiao, Jun Shi.
Uncertainty modeling for multi-center Autism Spectrum
Disorder classification using Takagi-Sugeno-Kang
fuzzy systems. IEEE Transactions on
Cognitive and Developmental Systems. 2022, 14(2): 730-739. (Highly Cited
Paper) [4] 施俊, 汪琳琳, 王珊珊, 陈艳霞, 王乾, 魏冬铭, 梁淑君, 彭佳林, 易佳锦, 刘盛锋, 倪东, 王明亮, 张道强, 沈定刚*. 深度学习在医学影像中的应用综述. 中国图象图形学报. 2020, 25(10): 1953-1981. (获评2021年《中国图象图形学报》优秀论文) [5] Xueying Zhou, Saisai
Ding, Wenhua Zhang, Juncheng Li, Jun Wang, Jiasheng Chen, Jun
Shi *. Dual-masked contrastive learning based
hypergraph foundation model for whole slide images. Pattern Recognition.
Accepted. [6] Xiangmin Han, Rundong
Xue, Jingxi Feng, yifan
feng, Shaoyi Du, Jun Shi*, Yue Gao*. Hypergraph foundation model for brain disease
diagnosis. IEEE Transactions on Neural Networks and Learning Systems.
Accepted. [7] Tianxiang Huang, Jing Shi, Ge Jin, Juncheng Li, Jun Wang, Qian Wang, Jun Du*, Jun Shi*. Topological GCN guided
improved conformer for detection of Hip landmarks from ultrasound images. IEEE Journal of Biomedical and
Health Informatics. Accepted. [8] Saisai Ding, Linjin
Li, Ge Jin, Jun Wang, Shihui Ying, Jun Shi*. HGMSurvNet:
A two-stage hypergraph learning network for multimodal cancer survival prediction.
Medical Image Analysis. 2025,
104: 103661. [9] Xueying Zhou, Ge Jin, Yang Liu, Juncheng Li, Jun Wang, Shihui
Ying, Yanyan Zheng, Jun Shi*. Multi-resolution based dual-channel UNet with cross clique for medical image dense prediction.
Expert Systems With
Applications. 2025, 276: 127190. [10] Jingbo He, Bo Peng, Shihui Ying, Juncheng Li, Yakang Dai*, Jun
Shi*. Dual-domain spatial-temporal reconstruction network for reconstruction
of cine CMR. Biomedical Signal Processing and Control. 2025, 107:
107836. [11] Juncheng Li, Hanhui
Yang, Qiaosi Yi, Minhua
Lu*, Jun Shi, Tieyong Zeng*. High-frequency modulated Transformer for multi-contrast
MRI super-resolution. IEEE Transactions on Medical Imaging. 2025,
44(7): 3089-3099. [12] Hao Zhang, Qi Wang, Jun Shi, Shihui
Ying*, Zhijie Wen. Deep unfolding network with spatial
alignment for multi-modal MRI reconstruction. Medical Image Analysis. 2025, 99: 103331. [13] Jiale Dun, Jun Wang*, Juncheng Li, Qianhui Yang, Wenlong Hang, Xiaofeng Lu, Shihui Ying, Jun
Shi. A trustworthy curriculum learning guided multi-target domain adaptation
network for Autism Spectrum Disorder classification.
IEEE Journal of Biomedical and Health
Informatics. 2025, 29(1): 310-323. [14] Weiyi
Lyu, Xinming Fang, Chaoyan
Huang, Minhua Lu*, Jun Wang, Jun Shi, Juncheng Li*. Fast MRI reconstruction: A thorough survey
from single-modal to multi-modal. Expert Systems With Applications. 2025, 283: 127703. [15] Saisai Ding, Juncheng
Li, Jun Wang, Shihui Ying, Jun Shi*. Multimodal co-attention fusion network with online
data augmentation for cancer subtype classification. IEEE Transactions on Medical Imaging. 2024, 43(11): 3977-3989. [16] Jian Wang, Liang Qiao, Shichong Zhou, Jin Zhou,
Jun Wang, Juncheng Li, Shihui
Ying, Cai Chang, Jun Shi*. Weakly
supervised lesion detection and diagnosis for breast cancers with partially annotated
ultrasound images. IEEE Transactions on
Medical Imaging. 2024, 43(7): 2509-2521. [17] Yuanming Zhang, Zheng Li, Xiangmin Han, Saisai Ding, Juncheng Li, Jun Wang, Shihui
Ying, Jun Shi*. Pseudo-data based self-supervised federated learning for classification
of histopathological images. IEEE
Transactions on Medical Imaging. 2024, 43(3): 902-915. [18] Qi Wang, Zhijie
Wen, Jun Shi, Qian Wang, Dinggang Shen, Shihui Ying*. Spatial
and modal optimal transport for fast cross-modal MRI reconstruction. IEEE Transactions on Medical Imaging. 2024, 43(11): 3924-3935. [19] Tianxiang Huang, Jing Shi*, Juncheng Li, Jun Wang, Jun Du, Jun Shi*. Involution Transformer based U-Net for landmark detection
in ultrasound images for diagnosis of infantile DDH. IEEE Journal of Biomedical and
Health Informatics. 2024, 28(8): 4797-4809. [20] Ke Sun, Jing Shi*, Ge Jin, Juncheng Li, Jun Wang, Jun Du, Jun Shi*. Dual-domain MIM based contrastive learning for
CAD of developmental dysplasia of the hip with ultrasound images. Biomedical Signal Processing and Control. 2024, 97: 106684. [21] Huili Zhang, Lehang
Guo, Juncheng Li, Jun Wang, Shihui
Ying, Jun Shi*. Multi-view disentanglement-based
bidirectional generalized distillation for diagnosis of liver cancers with ultrasound
images. Information Processing and
Management. 2024, 61: 103855. [22] Xiao Wang, Xinping
Ren, Ge Jin, Shihui Ying, Jun Wang, Juncheng Li, Jun
Shi*. B-mode ultrasound-based CAD by learning using privileged information
with dual-level missing modality completion. Computers in Biology and Medicine. 2024, 182: 109106. [23] Yinghua Fu, Junfeng
Liu, Jun Shi*. TSCA-Net:
Transformer based spatial-channel attention segmentation network for medical
images. Computers in Biology and
Medicine. 2024, 170: 107938. [24] Jiashi Cao, Qiong
Li, Huili Zhang, Yanyan
Wu, Xiang Wang, Saisai Ding, Song Chen, Shaochun Xu, Guangwen Duan, Defu Qiu, Jiuyi Sun, Jun Shi*, Shiyuan
Liu*. Radiomics model based on MRI to differentiate spinal multiple myeloma
from metastases: A two-center study. Journal
of Bone Oncology. 2024, 45: 100599. [25] Yan Hu, Jun Wang*, Hao Zhu, Juncheng Li, Jun
Shi. Cost-sensitive weighted contrastive learning based on graph convolutional
networks for imbalanced Alzheimer’s disease staging. IEEE Transactions on Medical Imaging. 2024, 43(9): 3126-3136. [26] Lipeng Cai, Jun Shi, Shaovi Du, Yue Gao, Shihui Ying*. Self-adaptive subspace representation from
a geometric intuition. Pattern
Recognition. 2024, 149: 110228. [27] Bodong Cheng, Juncheng
Li*, Jun Shi, Yingying Fang,
Guixu Zhang, Yin Chen, Tieyong
Zeng, Zhi Li*. WeaFU: Weather-informed image blind restoration
via multi-weather distribution diffusion. IEEE
Transactions on Circuits and Systems for Video Technology. 2024, 34(12): 13530-13542. [28] Juncheng Li, Bodong
Cheng, Ying Chen, Guangwei Gao, Jun Shi, Tieyong
Zeng. EWT: Efficient Wavelet-Transformer for single image denoising. Neural Networks. 2024, 177: 106378. [29] Yang Zhao, Bodong
Cheng, Najun Niu, Jun
Wang, Tieyong Zeng, Guixu
Zhang, Jun Shi, Juncheng Li*. Few sampling meshes-based
3D tooth segmentation via region-aware graph convolutional network. Expert Systems With
Applications. 2024, 252: 124255. [30] Juncheng Li*, Hanhui
Yang, Lok Ming Lui, Guixu Zhang, Jun Shi, Tieyong
Zeng. A lightweight self-ensemble feedback recurrent network for Fast MRI reconstruction.
International Journal of Machine
Learning and Cybernetics. 2024. [31] Juncheng Li, Bodong
Cheng, Najun Niu, Guangwei Gao, Shihui Ying, Jun Shi, Tieyong
Zeng. Fine-grained orthodontics segmentation model for 3D intraoral scan data.
Computers in Biology and Medicine. 2024,
168: 107821. [32] 赵阳, 李俊诚*, 成博栋, 牛娜君, 王龙光, 高广谓, 施俊. 深度学习在口腔医学影像中的应用与挑战. 中国图象图形学报. 2024, 29(3): 586-607. [33] Saisai Ding, Juncheng
Li, Jun Wang, Shihui Ying, Jun Shi*. Multi-scale efficient graph-Transformer for whole
slide image classification. IEEE Journal of Biomedical and Health Informatics. 2023, 27(12): 5926-5936. [34] Ronglin Gong, Jing Shi, Jian Wang, Jun
Wang, Jianwei Zhou, Xiaofeng
Lu, Jun Du*, Jun Shi*. Hybrid-supervised bidirectional transfer networks for computer-aided
diagnosis. Computers in Biology and
Medicine. 2023, 65: 107409. [35] Xiangmin Han, Bangming
Gong, Lehang Guo*, Jun Wang, Shihui
Ying, Shuo Li, Jun
Shi*. B-Mode ultrasound based CAD for liver cancers
via multi-view privileged information learning. Neural Networks. 2023,
164: 369-381. [36] Zhiyang Lu, Jian Wang, Zheng Li, Shihui Ying, Jun Wang, Jun Shi*, Dinggang Shen*. Two-stage
self-supervised cycle-consistency Transformer network for reducing slice gap
in MR images. IEEE Journal of Biomedical and Health Informatics. 2023, 27(7): 3337-3348. [37] Zheng Li, Shihui
Ying, Jun Wang, Hongjian He, Jun Shi*. Reconstruction of quantitative susceptibility mapping
from total field maps with local field maps guided UU-Net. IEEE Journal of Biomedical and
Health Informatics. 2023, 27(4): 2047-2058. [38] Huili Zhang, Lehang
Guo, Jun Wang, Shihui Ying, Jun Shi*. Multi-view feature transformation based SVM+ for
computer-aided diagnosis of liver cancers with ultrasound images. IEEE Journal of Biomedical and
Health Informatics. 2023, 27(3): 1512-1523. [39] Xiangmin Han, Jun Wang, Shihui Ying, Jun
Shi*, Dinggang Shen*. ML-DSVM+: a meta-learning
based deep SVM+ for computer-aided diagnosis. Pattern Recognition. 2023, 134: 109076. [40] Saisai Ding, Zhiyang Gao, Jun Wang, Minhua Lu*, Jun
Shi*. Fractal graph convolutional network with MLP-mixer based multi-path
feature fusion for classification of histopathological images. Expert Systems With
Applications. 2023, 212: 118793. [41] Guodong Chen, Zheng Li, Jian Wang, Jun
Wang, Shisuo Du, Jinghao
Zhou, Jun Shi*, Yongkang
Zhou*. An improved 3D KiU-Net for segmentation of liver
tumor. Computers in Biology and
Medicine. 2023, 160: 107006. [42] Jiaxin Huang#, Jun Shi#, Saisai Ding, Huili Zhang, Xueyan Wang, Shiyang Lin, Yanfen Xu, Mingjie Wei, Longzhong Liu, Xiaoqing Pei*. Deep learning model based
on dual-modal ultrasound and molecular data for predicting response to
neoadjuvant chemotherapy in breast cancer. Academic Radiology. 2023, 30: S50-S61. [43] Chunxiao Lai, Huili
Zhang, Jing Chen, Sihui Shao, Xin Li, Minghua Yao, Yi Zheng, Rong Wu*, Jun Shi*. Deep learning radiomics of ultrasonography for
differentiating sclerosing adenosis from breast cancer. Clinical Hemorheology and Microcirculation. 2023, 84: 153-163. [44] Qiong Wu, Jun Wang*, Zongqiong Sun, Lei Xiao, Wenhao
Ying, Jun Shi.
Immunotherapy efficacy prediction for non-small cell lung cancer using multi-view
adaptive weighted graph convolutional networks. IEEE Journal of Biomedical and
Health Informatics. 2023, 27(11): 5564-5575. [45] Hao Zhu, Jun Wang, Yinping Zhao, Minhua Lu, Jun Shi. Contrastive
multi-view composite graph convolutional networks based on contribution
learning for Autism Spectrum disorder
classification. IEEE Transactions on
Biomedical Engineering. 2023, 70(6): 1943-1954. [46] Zhaowu Lu, Jun Wang, Rui Mao, Minhua Lu, Jun
Shi. Jointly composite feature learning and Autism spectrum
disorder classification using deep multi-output Takagi-Sugeno-Kang fuzzy inference systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
2023, 20(1): 476-488. [47] Xin Wang, Jun Wang*, Fei Shan, Yiqiang Zhan, Jun
Shi, Dinggang Shen. Severity prediction of
pulmonary diseases using chest CT scans via cost-sensitive label multi-kernel
distribution learning. Computers in
Biology and Medicine. 2023, 159: 106890. [48] Hanhui Yang, Juncheng
Li, Lok Ming Lui, Shihui Ying, Jun Shi, Tieyong Zeng. Fast MRI reconstruction
via edge attention. Communications in
Computational Physics. 2023, 33(5): 1409-1431. [49] Jinhe Dong, Jun Shi, Yue Gao, Shihui Ying.
GAME: Gaussian mixture error based meta learning architecture. Neural Computing and Applications. 2023,
35, 20445-20461. [50] Hanlin Xu, Bohan
Zhang, Yaxin Chen, Fengzhen
Zeng, Wenjuan Wang, Ziyi
Chen, Ling Cao, Jun Shi,
Jun Chen, Xiaoxia Zhu, Yu Xue, Rui He, Minbiao Ji, Yinghui Hua. Type II collagen facilitates gouty arthritis
by regulating MSU crystallization and inflammatory cell recruitments. Annals of the Rheumatic Diseases. 2023,
82(3): 416-427. [51] Xiangmin Han, Xiaoyan
Fei, Jun Wang, Tao Zhou, Shihui Ying, Jun Shi*, Dinggang
Shen*. Doubly supervised transfer classifier for computer-aided diagnosis
with imbalanced modalities. IEEE
Transactions on Medical Imaging. 2022, 41(8): 2009-2020. [52] Jun Wang, Fengyexin
Zhang, Xiuyi Jia, Xin Wang, Han Zhang, Shihui Ying, Qian Wang, Jun Shi*, Dinggang Shen*. Multi-class
ASD classification via label distribution learning with class-shared and class-specific
decomposition. Medical Image Analysis.
2022, 75: 102294. [53] Yanbin He, Zhiyang
Lu, Jun Wang, Shihui Ying, Jun Shi*. A self-supervised learning based
channel attention MLP-Mixer network for motor imagery decoding. IEEE Transactions on Neural Systems &
Rehabilitation Engineering. 2022, 30: 2406-2417. [54] Zhiyang Lu, Jun Li, Chaoyue Wang, Rongjun Ge, Lili
Chen, Hongjian He, Jun Shi*. S2Q-Net: mining the high-pass filtered phase data
in susceptibility weighted imaging for quantitative susceptibility mapping. IEEE Journal of Biomedical and
Health Informatics. 2022, 26(8): 3938-3949. [55] Zhiyang Gao, Zhiyang
Lu, Jun Wang, Shihui Ying, Jun Shi*. A convolutional neural network and graph
convolutional network based framework for
classification of breast histopathological images. IEEE Journal of Biomedical and
Health Informatics. 2022, 26(7): 3163-3173. [56] Ronglin Gong, Xiangmin
Han, Jun Wang, Shihui Ying, Jun Shi*. Self-supervised bi-channel Transformer networks
for computer-aided diagnosis. IEEE Journal of Biomedical and Health Informatics. 2022, 26(7): 3435-3446. [57] Bangming Gong, Jing Shi, Xiangmin Han, Huan Zhang, Yuemin
Huang, Liwei Hu, Jun Wang, Jun Du*, Jun
Shi*. Diagnosis of infantile hip dysplasia with B-mode ultrasound via
two-stage meta-learning based deep exclusivity regularized machine. IEEE Journal of Biomedical and Health
Informatics. 2022, 26(1): 334-344. [58] Ronglin Gong, Linlin
Wang, Jun Wang, Binjie Ge, Hang Yu, Jun Shi*. Self-distilled supervised
contrastive learning for diagnosis of breast cancers with histopathological images.
Computers in Biology and Medicine. 2022, 146: 105641. [59] Weijie Kang, Min Ji, Huili Zhang, Hua Shi, Tianchao
Xiang, Yaqi Li, Ye Fang, Qi Qi,
Junbo Wang, Jian Shen, Liangfeng
Tang, Xiaoxiong Liu, Yingzi
Ye, Xiaoling Ge, Xiang Wang, Hong Xu, Zhongwei Qiao*, Jun Shi*, Jia Rao*. A novel
clinical-radiomics model predicted renal lesions and deficiency in children
on diffusion-weighted MRI. Frontiers in
Physics. 2022. [60] Jun Wang, Zhuangzhuang
Zhao, Zhaohong Deng, Kup-Sze
Choi, Lejun Gong, Jun Shi, Shitong Wang.
Manifold-regularized multitask fuzzy system modeling with low-rank and sparse
structures in consequent parameters. IEEE
Transactions on Fuzzy Systems. 2022, 30(5): 1486-1500. [61] Weichang Ding, Jun Wang*, Weijun Zhou, Shichong Zhou, Cai
Chang, Jun Shi. Joint localization
and classification of breast cancer in B-mode ultrasound imaging via collaborative
learning with elastography. IEEE
Journal of Biomedical and Health Informatics. 2022, 26(9): 4474-4485. [62] 贡荣麟, 施俊*, 周玮珺, 汪程. 面向乳腺超声计算机辅助诊断的两阶段深度迁移学习. 中国图象图形学报. 2022, 27(3): 898-910. [63] Xing Wu*, Cheng Chen, Mingyu
Zhong, Jianjia Wang, Jun Shi*. COVID-AL: the diagnosis of COVID-19 with deep
active learning. Medical Image Analysis.
2021, 63: 101913. [64] Xiaoyan Fei, Shichong
Zhou, Xiangmin Han, Jun Wang, Shihui
Ying, Cai Chang, Weijun Zhou, Jun Shi*. Doubly supervised parameter transfer classifier
for diagnosis of breast cancer with imbalanced ultrasound imaging modalities.
Pattern Recognition. 2021, 120:
108139. [65] Huili Zhang, Lehang
Guo, Dan Wang, Jun Wang, Lili Bao, Shihui Ying, Huixiong Xu*, Jun
Shi*. Multi-source transfer learning via multi-kernel support vector
machine plus for B-mode ultrasound-based computer-aided diagnosis of liver
cancers. IEEE Journal of Biomedical and
Health Informatics. 2021, 25(10): 3874-3885. [66] Zheng Li, Jun Li, Chaoyue Wang, Zhiyang
Lu, Jun Wang,
Hongjian He*, Jun Shi*. Meta-learning
based interactively connected clique U-Net for quantitative susceptibility mapping.
IEEE Transactions on Computational
Imaging. 2021, 7: 1385-1399. [67] Zheng Li, Chaofeng
Wang, Jun Wang, Shihui Ying, Jun Shi*. Lightweight adaptive weighted network for single
image super-resolution. Computer Vision
and Image Understanding. 2021, 211: 103254. [68] Shanshan Wang#, Guohua Cao#, Yan Wang#, Shu Liao#, Qian Wang#, Jun Shi#, Cheng Li, Dinggang Shen*. Review and prospect: artificial intelligence
in advanced medical imaging. Frontiers
in Radiology. 2021, 1: 781868. [69] 应时辉、杨菀、杜少毅、施俊*. 基于深度学习的医学影像配准综述. 模式识别与人工智能. 2021,
34(4): 287-299. [70] Weiwen Wu, Jun Shi, Hengyong Yu, Weifei Wu*, Varut Vardhanabhuti*. Tensor gradient L0-norm minimization
based low-dose CT and its application to COVID-19. IEEE Transactions on Instrumentation & Measurement. 2021, 70:
4503012. [71] Jun Wang, Lichi Zhang, Qian
Wang*, Lei Chen, Jun Shi,
Xiaobo Chen, Zuoyong Li, and Dinggang
Shen*. Multi-class ASD classification based on functional connectivity and
functional correlation tensor via multi-source domain adaptation and
multi-view sparse representation. IEEE
Transactions on Medical Imaging. 2020, 39(10): 3137-3147. [72] Xiaoyan Fei, Jun Wang, Shihui Ying, Zhongyi Hu, Jun Shi*. Projective parameter
transfer based sparse multiple empirical kernel learning machine for
diagnosis of brain disease. Neurocomputing.
2020, 413: 271-283. [73] Xiaoyan Fei, Lu Shen, Shihui Ying, Yehua Cai, Qi
Zhang, Wentao Kong, Weijun
Zhou, Jun Shi*. Parameter
transfer deep neural network for single-modal B-mode ultrasound-based
computer aided diagnosis. Cognitive
Computation. 2020, 12: 1252-1264. [74] Lu
Shen, Jun Shi*, Yun Dong, Shihui Ying, Yaxin Peng, Lu
Chen, Qi Zhang, Hedi An, Yingchun
Zhang. An improved deep polynomial network algorithm for transcranial sonography based diagnosis of Parkinson’s disease. Cognitive Computation. 2020, 12: 553-562. [75] 贡荣麟, 施俊*, 王骏. 基于混合监督双通道反馈U-Net的乳腺超声图像分割. 中国图象图形学报. 2020, 25(10): 2206-2217. [76] 沈璐, 王倩婷, 施俊*. 基于特权信息集成学习的精神分裂症单模态神经影像计算机辅助诊断. 生物医学工程学杂志, 2020, 37(3): 405-411. [77] Jun Shi, Zeyu Xue, Yakang Dai, Bo Peng, Yun Dong, Qi Zhang, Yingchun Zhang. Cascaded multi-column RVFL+ classifier
for single-modal neuroimaging-based diagnosis of Parkinson’s disease. IEEE Transactions on Biomedical
Engineering. 2019, 66(8): 2362-2371. [78] Jun Shi, Xiao Zheng, Jinjie
Wu, Yan Li, Qi Zhang, Shihui Ying. Quaternion Grassmann average network for learning representation of histopathological
image. Pattern Recognition. 2019,
89: 67-76. [79] Jun Shi, Zheng Li, Shihui
Ying, Chaofeng Wang, Qi Zhang, Pingkun
Yan. MR image super-resolution via wide residual networks with fixed skip
connection. IEEE Journal of Biomedical
and Health Informatics. 2019, 23(3): 1129-1140. [80] Yan Li, Fanqing
Meng, Jun Shi*. Learning
using privileged information improves neuroimaging-based CAD of Alzheimer's
disease: a comparative study. Medical
& Biological Engineering & Computing. 2019, 57(7): 1605-1616. [81] Xiaoyan Fei, Yun Dong, Hedi An, Qi Zhang, Yingchun
Zhang, Jun Shi*. Impact of
region of interest size on transcranial sonography based
computer-aided diagnosis for Parkinson’s disease. Mathematical Biosciences and Engineering. 2019, 16(5): 5640-5651. [82] Qi Zhang, Shuang Song, Yang
Xiao, Shuai Chen, Jun Shi, Hairong Zheng. Dual-modal artificially intelligent
diagnosis of breast tumors on both shear-wave elastography and B-mode
ultrasound using deep polynomial networks. Medical Engineering and Physics, 2019, 64: 1-6. [83] Bangming Gong, Jun Shi*, Shihui Ying, Yakang Dai, Qi Zhang, Yun Dong, Hedi
An, Yingchun Zhang. Neuroimaging-based diagnosis of
Parkinson’s disease with deep neural mapping large margin distribution
machine. Neurocomputing. 2018, 320:
141-149. [84] Jun Shi, Qingping
Liu, Chaofeng Wang, Qi Zhang, Shihui
Ying, Haoyu Xu. Super-resolution reconstruction of
MR image with a novel residual learning network algorithm. Physics in Medicine & Biology.
2018, 63(8):085011. [85] Lehang Guo, Dan Wang, Yiyi Qian, Xiao
Zheng, Chongke Zhao, Xiaolong
Li, Xiaowan Bo, Wenwen
Yue, Qi Zhang, Jun Shi*, Huixiong Xu. A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with
contrast enhanced ultrasound images. Clinical
Hemorheology and Microcirculation. 2018, 69(3): 343-354. [86] Shihui Ying, Zhijie
Wen, Jun Shi, Yaxin Peng, Jigen Peng, Hong Qiao. Manifold preserving: an intrinsic approach for semi-supervised
distance metric learning. IEEE
Transactions on Neural Networks and Learning Systems. 2018, 29(7):
2731-2742. [87] Qi Zhang, Yue Liu, Hong Han, Jun Shi, Wenping
Wang. Artificial intelligence based diagnosis for
cervical lymph node malignancy using the point-wise gated Boltzmann machine. IEEE Access. 2018, 6: 60605 - 60612. [88] Meihui Qiu, Huifeng
Zhang, David Mellor, Jun Shi,
Chuangxin Wu, Yueqi
Huang, Jianye Zhang, Ting Shen, Daihui
Peng. Aberrant neural activity in patients with bipolar depressive disorder
distinguishing to the unipolar depressive disorder: a resting-state
functional magnetic resonance imaging study. Frontiers in Psychiatry. 2018, 9: 238. [89] Jun Shi, Jinjie Wu,
Yan Li, Qi Zhang, Shihui Ying. Histopathological image
classification with color pattern random binary hashing based PCANet and matrix-form classifier. IEEE Journal of Biomedical and Health Informatics. 2017, 21(5):
1327-1337. [90] Junjie
Zhang, Jie Yin, Qi Zhang, Jun
Shi*, Yan Li. Robust sound event
classification with bilinear multi-column ELM-AE and two-stage ensemble
learning. EURASIP Journal on Audio,
Speech, and Music Processing. 2017, 11. [91] Huaipeng Dong, Qi Zhang, Jun Shi. Intensity
inhomogeneity compensation and tissue segmentation for magnetic resonance
imaging with noise-suppressed multiplicative intrinsic component
optimization. Optical Engineering.
2017, 56(12): 123103. [92] Qi Zhang, Jing Yao, Yehua Cai, Limin Zhang, Yishuo Wu, Jingyu Xiong, Jun Shi, Yuanyuan Wang, Yi
Wang. Elevated hardness of peripheral gland on real-time elastography is an
independent marker for high-risk prostate cancers. La Radiologia Medica. 2017, 122(12):
944-951. [93] Qi Zhang, Yang Xiao, Jingfeng Suo, Jun Shi, Jinhua Yu, Yi Guo, Yuanyuan Wang, Hairong Zheng. Sonoelastomics
for breast tumor classification: a radiomics approach with clustering-based feature
selection on sonoelastography. Ultrasound in Medicine and Biology. 2017, 43(5): 1058-1069. [94] Qi Zhang, Jingfeng
Suo, Wanying Chang, Jun Shi, Man Chen. Dual-modal computer-assisted evaluation
of axillary lymph node metastasis in breast cancer patients on both real-time
elastography and B-mode ultrasound. European
Journal of Radiology, 2017, 95, 66-74. [95] Qi Zhang, Congcong
Yuan, Wei Dai, Lei Tang, Jun Shi,
Zuoyong Li, Man Chen. Evaluating pathologic
response of breast cancer to neoadjuvant chemotherapy with computer-extracted
features from contrast-enhanced ultrasound videos. Physica Medica, 2017, 39, 156-163. [96] Qi Zhang, Yehua
Cai, Yinghui Hua, Jun Shi, Yuanyuan Wang, Yi Wang. Sonoelastography
shows that Achilles tendons with insertional tendinopathy are harder than
asymptomatic tendons. Knee Surgery,
Sports Traumatology, Arthroscopy. 2017, 25: 1839-1848. [97] Jun Shi, Shichong
Zhou, Xiao Liu, Qi Zhang, Minhua Lu, Tianfu Wang. Stacked
deep polynomial network based representation learning
for tumor classification with small ultrasound image dataset. Neurocomputing. 2016, 194: 87-94. [98] Qi Zhang, Yang Xiao, Wei Dai, Jingfeng Suo, Congzhi Wang, Jun Shi, Hairong
Zheng. Deep learning based classification of breast
tumors with shear-wave elastography. Ultrasonics.
2016, 72: 150-157. [99] Jun Shi, Xiao Liu, Yan Li, Qi Zhang, Yingjie
Li, Shihui Ying. Multi-channel EEG based sleep
stage classification with joint collaborative representation and multiple
kernel learning. Journal of Neuroscience
Methods. 2015, 254: 94-101. [100] Jun Shi, Qikun
Jiang, Qi Zhang, Qinghua Huang, Xuelong
Li. Sparse kernel entropy component analysis for dimensionality reduction of biomedical
data. Neurocomputing. 2015, 168:
930-940. [101] Jun Shi, Qikun
Jiang, Rui Mao, Minhua Lu, Tianfu Wang. FR-KECA: fuzzy
robust kernel entropy component analysis.
Neurocomputing. 2015, 149: 1415-1423. [102] Jun Shi, Yi Li, Jie Zhu, Haojie
Sun, Yin Cai. Joint sparse coding based spatial pyramid matching for classification
of color medical image. Computerized
Medical Imaging and Graphics. 2015, 41: 61-66. [103] Qi Zhang, Chaolun
Li, Hong Han, Wei Dai, Jun Shi,
Yuanyuan Wang, Wenping Wang.
Spatiotemporal quantification of carotid plaque neovascularization on
contrast-enhanced ultrasound: correlation with visual grading and
histopathology. European Journal of
Vascular and Endovascular Surgery. 2015, 50(3): 289-296. [104] Qi Zhang, Chaolun
Li, Moli Zhou, Yu Liao, Chunchun
Huang, Jun Shi, Yuanyuan
Wang, Wenping Wang. Quantification of carotid
plaque elasticity and intraplaque neovascularization using contrast-enhanced
ultrasound and imager egistration-based
elastography. Ultrasonics. 2015, 62:
253-262. [105] Huali Chang, Zhenping
Chen, Qinghua Huang, Jun Shi, Xuelong Li. Graph-based
learning for segmentation of 3D ultrasound images. Neurocomputing. 2015, 151: 632-644. [106] Jun Shi, Yin Cai, Jie Zhu, Jin Zhong, Fei
Wang. SEMG-based hand motion recognition using cumulative residual entropy
and extreme learning machine. Medical
& Biological Engineering & Computing. 2013, 51(4): 417-427. [107] Shichong Zhou, Jun Shi*, Jie Zhu, Yin Cai, Ruiling
Wang. Shearlet-based texture feature extraction for
classification of breast tumor in ultrasound image. Biomedical Signal Processing and Control. 2013, 8(6): 688-696. [108] Jun Shi, Jingyi Guo, Shuxian
Hu, Yongping Zheng. Recognition of finger flexion motion from ultrasound image:
a feasibility study. Ultrasound in
Medicine and Biology. 2012, 38(10): 1695-1704. [109] Jun Shi, Qian Chang, Yongping Zheng.
Feasibility of controlling a prosthetic hand using sonomyography
signal in real time: a preliminary study. Journal
of Rehabilitation Research and Development. 2010, 47(2): 87-98. [110] Jiehui Jiang, Zhuangzhi
Yan, Jun Shi, et al. A
mobile monitoring system of blood pressure for underserved in China by
information and communication technology service. IEEE Transactions on Information Technology in Biomedicine. 2010,
14(3): 748-757. [111] Xin Chen, Yongping Zheng, Jingyi
Guo, Jun Shi. Sonomyography (SMG) Control for Powered Prosthetic Hand:
A Study with Normal Subjects. Ultrasound
in Medicine and Biology. 2010, 36(7): 1076-1088. [112] Jun Shi, Yongping Zheng, Xin Chen, Hongbo Xie. Modeling the relationship between wrist angle
and muscle thickness during wrist flexion-extension based on the bone-muscle
lever system: a comparison study. Medical
Engineering and Physics. 2009, 31(10): 1125-1160. [113] Hongbo Xie, Yongping Zheng, Jingyi
Guo, Xin Chen, Jun Shi. Estimation
of wrist angle from sonomyography using support
vector machine and artificial neural network models. Medical Engineering and Physics. 2009, 31(3): 384-391. [114] Jun Shi, Yongping Zheng, Qinghua
Huang, Xin Chen. Continuous monitoring of sonomyography,
electromyography and torque generated by normal upper arm muscles during
isometric contraction: sonomyography assessment for
arm muscles. IEEE Transactions on
Biomedical Engineering. 2008, 55(3): 1191-1198. [115] Jun Shi, Yongping
Zheng, Xin Chen, et al. Assessment of muscle fatigue using sonomyography:
muscle thickness change detected from ultrasound images. Medical Engineering and Physics. 2007, 29(4): 472-479. [116] Yongping Zheng, Matthew Chan, Jun Shi, et al. Sonomyography: monitoring morphological changes of
forearm muscles in actions with the feasibility for the control of powered
prosthesis. Medical Engineering and
Physics. 2006, 28: 405-415. [117] Yongping Zheng, Jun Shi, et al. Dynamic
Depth-dependent Osmotic Swelling and Solute Diffusion in Articular Cartilage
Monitored using Real-time Ultrasound.
Ultrasound in Medicine and Biology. 2004, 30 (6): 841-849. [118] Yongping Zheng, SL Bridal, Jun Shi, et al. High resolution ultrasound elastomicroscopy
imaging of soft tissues: System development and feasibility. Physics in Medicine and Biology. 2004,
49(17): 3925-3938. 代表性会议论文: [1] Ke
Sun, Jing Shi, Jun Du, Qian Wang, Jun
Shi*. Hybrid symmetry Mamba network for ultrasound-based CAD of developmental
dysplasia of the Hip. The 47th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBC). 2025. [2] Tianxiang
Huang, Jing Shi, Ge Jin, Juncheng Li, Jun Wang, Jun
Du*, Jun Shi*. Topological
GCN for improving detection of hip landmarks from B-mode ultrasound Images. The 27th International Conference on
Medical Image Computing and Computer Assisted Intervention (MICCAI). 2024 (Oral presentation, 2.7%). [3] Saisai Ding, Jun Wang, Juncheng Li, Jun
Shi*. Multi-scale prototypical Transformer for whole slide image classification. The 26th International Conference on
Medical Image Computing and Computer Assisted Intervention (MICCAI). 2023. [4] Yanbin He, Zhiyang
Lu, Jun Wang, Jun Shi*. A channel
attention based MLP-Mixer network for motor imagery decoding with EEG. 2022 IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP). 2022. [5] Ronglin Gong, Shihui
Ying, Jun Shi*. Task-driven
self-supervised bi-channel networks learning for diagnosis of breast cancers
with mammography. 2022 IEEE
International Conference in Image Processing (ICIP). 2022. [6] Zhiyang
Gao, Jun Wang, Jun Shi*. GQ-GCN:
Group quadratic graph convolution network for classification of histopathological
images. The 24th International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI). 2021. [7] Zhiyang
Lu, Zheng Li, Jun Wang, Jun Shi*, Dinggang
Shen*. Two-stage self-supervised cycle-consistency
network for reconstruction of thin-slice MR images. The 24th International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI). 2021. [8] Zhiyang
Lu, Jun Li, Zheng Li, Hongjian He, Jun Shi*. Reconstruction of
quantitative susceptibility maps from phase of susceptibility weighted
imaging with cross-connected Ψ-Net. The
2021 IEEE International Symposium on
Biomedical Imaging (ISBI). 2021. [9] Xiangmin
Han, Jun Wang, Weijun Zhou, Cai Chang, Shihui Ying, Jun
Shi*. Deep doubly supervised transfer network for diagnosis of breast
cancer with imbalanced ultrasound imaging modalities. The 23rf International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI). 2020. [10] Bangming
Gong, Lu Shen, Cai Chang, Shichong Zhou, Weijun Zhou, Shuo Li, Jun Shi*. Bi-modal
ultrasound breast cancer diagnosis via multi-view deep neural network SVM. IEEE International Symposium on Biomedical
Imaging (ISBI). 2020. [11] Zheng Li, Qingping
Liu, Yiran Li, Qiu Ge, Yuanqi
Shang, Donghui Song, Ze Wang*, Jun Shi*. A two-stage multi-loss super-resolution network for
arterial spin labeling magnetic resonance imaging. The 22nd International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI). 2019. (Graduate Student Travel Award) [12] Jun Wang, Ying Zhang, Tao Zhou,
Zhaohong Deng, Huifang Huang, Shitong
Wang, Jun Shi, Dinggang Shen. Interpretable feature learning using multi-output
Takagi-Sugeno-Kang fuzzy system for multi-center
ASD diagnosis. The 22nd International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI). 2019. [13] Xiaoyan Fei, Weijun
Zhou, Lu Shen, Cai Chang, Wentao Kong, Shichong Zhou, Jun
Shi*, Ultrasound-based diagnosis of breast tumor with parameter
transfer multilayer kernel extreme learning machine. The 41st Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBS). 2019. [14] Jun Shi, Minjun Yan, Yun Dong, Xiao Zheng, Qi Zhang, Hedi An. Multiple kernel
learning based classification of Parkinson’s disease with multi-modal
transcranial sonography. The 40th
Annual International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBS). 2018. (Oral Representation) [15] Lu Shen, Jun Shi*, Bangming Gong, Yingchun Zhang,
Yun Dong, Qi Zhang, Hedi An. Multiple
empirical kernel mapping based broad learning system for classification of
Parkinson’s disease with transcranial sonography. The 40th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBS). 2018. (Oral Representation) [16] Fanqing Meng, Jun Shi*, Bangming Gong, Qi Zhang, Lehang
Guo, Dan Wang, Huixiong Xu*. B-mode ultrasound based diagnosis of liver cancer with CEUS images
as privileged information. The
40th Annual International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBS). 2018. (Oral Representation) [17] Zeyu Xue, Jun Shi*, Yakang Dai, Yun Dong, Qi Zhang, Yingchun Zhang. Transcranial sonography
based diagnosis of Parkinson’s disease via cascaded kernel RVFL+. The 40th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBS). 2018. [18] Haohao Xu, Qi
Zhang, Huaipeng Dong, Xiyuan
Jiang, Jun Shi. Suppression
of ultrasonography using maximum likelihood estimation and weighted nuclear norm
minimization. The 40th Annual
International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBS). 2018. [19] Qingping
Liu, Jun Shi*, Ze Wang. Reconstructing high-resolution arterial spin labeling perfusion
images via convolutional neural networks residual-learning based methods. Joint Annual Meeting ISMRM-ESMRMB.
2018. [20] 钱奕奕, 施俊*, 郑晓, 张麒, 郭乐航, 王丹, 徐辉雄. 基于多模态超声成像的肝肿瘤计算机辅助诊断. 2017中国生物医学工程大会,青年论文竞赛三等奖. (Oral Representation) [21] Xiao
Zheng, Jun Shi*, Qi Zhang, Shihui Ying, Yan Li. Improving
MRI-based diagnosis of Alzheimer’s disease via an ensemble privileged
information learning algorithm. 2017 IEEE
International Symposium on Biomedical Imaging (ISBI). 2017. (Oral Representation) [22] Chaofeng Wang, Jun Shi*, Qi Zhang, Shihui
Ying. Histopathological image classification
with bilinear convolutional neural networks. The 39th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [23] Yiyi
Qian, Jun Shi*, Xiao Zheng, Qi Zhang, Lehang Guo, Dan
Wang, Huixiong Xu. Multimodal ultrasound imaging based diagnosis of liver cancers with a two-stage
multi-view learning framework. The 39th Annual International Conference of the
IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [24] Lehang Guo, Dan Wang, Huixiong Xu, Yiyi Qian, Chaofeng
Wang, Xiao Zheng, Qi Zhang, Jun
Shi*. CEUS-based classification of
liver tumors with deep canonical
correlation analysis and multi-kernel learning. The 39th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [25] Jinjie Wu, Jun Shi*, Yan Li, Jingfeng Suo, Qi Zhang. Histopathological
image classification using random binary hashing based PCANet
and bilinear classifier. The 2016 European
Signal Processing Conference (EUSIPCO). 2016. (Oral Representation) [26] Xiao
Zheng, Jun Shi*, Yan Li, Xiao Liu, Qi Zhang. Multi-modality stacked deep
polynomial network based feature learning for
Alzheimer’s disease diagnosis. 2016 IEEE
International Symposium on Biomedical Imaging (ISBI). 2016. [27] Xiao
Zheng, Jun Shi*, Shihui
Ying, Qi Zhang, Yan Li. Improving single-modal neuroimaging based diagnosis of brain disorders via boosted
privileged information learning framework. 2016 MICCAI Workshop on Machine
Learning in Medical Imaging (MLMI).
2016. [28] Jinjie Wu, Jun Shi*, Shihui
Ying, Qi Zhang, Yan Li. Learning representation
for histopathological image with quaternion Grassmann
average network. 2016
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI).
2016. [29] Xiao Liu, Jun Shi*, Qi Zhang. Tumor classification by deep polynomial network and
multiple kernel learning on small ultrasound image dataset. 2015 MICCAI Workshop on Machine
Learning in Medical Imaging (MLMI).
2015. [30] Jie Zhu, Jun Shi*. Hessian regularization based semi-supervised dimensionality
reduction for neuroimaging data of Alzheimer’s disease. 2014 IEEE International Symposium on Biomedical Imaging (ISBI).
2014. [31] Xiao Liu, Jun Shi*, Shichong Zhou, Minhua Lu. An iterated Laplacian based semi-supervised dimensionality
reduction for classification of breast cancer on ultrasound images. The 36th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). 2014. [32] Qikun Jiang, Jun Shi*. Sparse kernel entropy component analysis for dimensionality
reduction of neuroimaging data. The 36th Annual International Conference of the
IEEE Engineering in Medicine and Biology Society (EMBS). 2014. [33] Jun Shi, Yin Cai. Joint sparse coding spatial pyramid
matching for classification of color blood cell image. 2013 MICCAI Workshop on Machine Learning in Medical Imaging (MLMI).
2013. |
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Jun Shi, Ph.D,
Professor, Deputy Dean |
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Office: |
825
Xiangying Building, 333 Nanchen
Road, Shanghai University, Shanghai |
|
Mail Address(Zip Code): |
Box 83, 99 Shangda Road, Shanghai
University, Shanghai (200444) |
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Phone: |
86-21-66137269/66138178 |
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Email: |
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URL: |
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Machine Learning (Deep Learning), Medical Image (Ultrasound, MRI)
Analysis, Biomedical Signal (EEG, EEG) Processing, Rehabilitation Engineering Educational Background: 09/1996 ~ 06/2005,
Department of Electronic Engineering and Information Science, University of
Science and Technology of China (USTC) Working Experiences: 05/2005 – , School of Communication and Information Engineering, Shanghai
Institute for Advanced Communication and Data Science, Shanghai University,
Lecturer, Associate Professor, Professor 01/2011 –
01/2012, BRIC, University of North Carolina at Chapel Hill, Visiting Scholar,
Hosted by Professor Dinggang Shen 07/2009 –
10/2009, Hongkong Polytechnic University, Visiting Scholar, Hosted by
Professor Yongping Zheng 07/2004 –
11/2004, Hongkong Polytechnic University, Research Assistant 07/2002 –
04/2003, Hongkong Polytechnic University, Research Assistant Grants
and Funding: National
Natural Science Foundation of China (NSFC), Key Program of NSFC (Co-PI), Special
Fund for Basic Research on Scientific Instruments of NSFC (Co-PI), Shanghai
Municipal Natural Science Foundation, Innovation Program of Shanghai
Municipal Education Commission, etc. Selected Journal Publications: [1] Jun Shi, Xiao Zheng, Yan Li, Qi Zhang,
Shihui Ying. Multimodal neuroimaging feature
learning with multimodal stacked deep polynomial networks for diagnosis of Alzheimer's
disease. IEEE Journal of Biomedical and
Health Informatics. 2018, 22(1): 173-183. (Highly Cited Paper) [2] Feng Shi#, Jun Wang#,
Jun Shi#, Ziyan Wu, Qian Wang, Zhenyu
Tang, Kelei He, Yinghuan
Shi, Dinggang Shen*. Review of artificial
intelligence techniques in imaging data acquisition, segmentation and
diagnosis for COVID-19. IEEE Reviews in
Biomedical Engineering. 2021, 14: 4-15. (#Equal Contribution, Highly Cited Paper) [3] Zhongyi Hu, Jun Wang, Chunxiang Zhang, Zhenzhen Luo, Xiaoqing Luo, Lei Xiao, Jun Shi. Uncertainty modeling
for multi-center Autism Spectrum Disorder classification
using Takagi-Sugeno-Kang fuzzy systems. IEEE Transactions on Cognitive and
Developmental Systems. 2022, 14(2): 730-739. (Highly Cited Paper) [4] Xueying Zhou, Saisai Ding, Wenhua Zhang, Juncheng Li, Jun Wang, Jiasheng
Chen, Jun Shi *. Dual-masked
contrastive learning based hypergraph foundation model
for whole slide images. Pattern Recognition. Accepted. [5] Xiangmin Han, Rundong Xue, Jingxi
Feng, yifan feng, Shaoyi
Du, Jun Shi*, Yue Gao*.
Hypergraph foundation model for brain disease diagnosis. IEEE Transactions
on Neural Networks and Learning Systems. Accepted. [6] Tianxiang Huang, Jing Shi, Ge Jin, Juncheng Li,
Jun Wang, Qian Wang, Jun Du*, Jun
Shi*. Topological GCN guided improved conformer for detection of Hip landmarks
from ultrasound images. IEEE Journal of Biomedical and
Health Informatics. Accepted. [7] Saisai Ding, Linjin Li, Ge Jin, Jun Wang, Shihui Ying, Jun
Shi*. HGMSurvNet: A two-stage hypergraph learning
network for multimodal cancer survival prediction. Medical Image Analysis.
2025,
104: 103661. [8] Xueying Zhou, Ge Jin, Yang Liu, Juncheng Li,
Jun Wang, Shihui Ying, Yanyan
Zheng, Jun Shi*. Multi-resolution
based dual-channel UNet with cross clique for medical
image dense prediction. Expert Systems With Applications. 2025, 276: 127190. [9] Jingbo He, Bo Peng, Shihui Ying, Juncheng Li, Yakang Dai*, Jun Shi*. Dual-domain spatial-temporal
reconstruction network for reconstruction of cine CMR. Biomedical Signal
Processing and Control. 2025, 107: 107836. [10] Juncheng Li, Hanhui Yang, Qiaosi
Yi, Minhua Lu*, Jun Shi, Tieyong Zeng*. High-frequency
modulated Transformer for multi-contrast MRI super-resolution. IEEE
Transactions on Medical Imaging. 2025, 44(7): 3089-3099. [11] Hao Zhang, Qi Wang, Jun Shi, Shihui
Ying*, Zhijie Wen. Deep unfolding network with spatial
alignment for multi-modal MRI reconstruction. Medical Image Analysis. 2025, 99: 103331. [12] Jiale Dun, Jun Wang*, Juncheng Li, Qianhui Yang, Wenlong Hang, Xiaofeng Lu, Shihui Ying, Jun
Shi. A trustworthy curriculum learning guided multi-target domain adaptation
network for Autism Spectrum Disorder classification.
IEEE Journal of Biomedical and Health
Informatics. 2025, 29(1): 310-323. [13] Weiyi Lyu, Xinming Fang, Chaoyan Huang, Minhua Lu*, Jun
Wang, Jun Shi, Juncheng Li*. Fast MRI reconstruction: A thorough survey
from single-modal to multi-modal. Expert Systems With
Applications. 2025, 283: 127703. [14] Saisai Ding, Juncheng Li, Jun Wang, Shihui Ying, Jun
Shi*. Multimodal co-attention fusion network with online data augmentation
for cancer subtype classification. IEEE
Transactions on Medical Imaging. 2024, 43(11): 3977-3989. [15] Jian Wang, Liang Qiao, Shichong Zhou, Jin Zhou,
Jun Wang, Juncheng Li, Shihui
Ying, Cai Chang, Jun Shi*. Weakly
supervised lesion detection and diagnosis for breast cancers with partially annotated
ultrasound images. IEEE Transactions on
Medical Imaging. 2024, 43(7): 2509-2521. [16] Yuanming Zhang, Zheng Li, Xiangmin Han, Saisai Ding, Juncheng Li, Jun
Wang, Shihui Ying, Jun Shi*. Pseudo-data based self-supervised
federated learning for classification of histopathological images. IEEE Transactions on Medical Imaging. 2024, 43(3): 902-915. [17] Qi Wang, Zhijie
Wen, Jun Shi, Qian Wang, Dinggang Shen, Shihui Ying*. Spatial
and modal optimal transport for fast cross-modal MRI reconstruction. IEEE Transactions on Medical Imaging. 2024, 43(11): 3924-3935. [18] Tianxiang Huang, Jing Shi*, Juncheng Li, Jun
Wang, Jun Du, Jun Shi*. Involution
Transformer based U-Net for landmark detection in ultrasound images for diagnosis
of infantile DDH. IEEE Journal of Biomedical and
Health Informatics. 2024, 28(8): 4797-4809. [19] Ke Sun, Jing Shi*, Ge Jin, Juncheng Li, Jun Wang, Jun Du, Jun Shi*. Dual-domain MIM based contrastive learning for
CAD of developmental dysplasia of the hip with ultrasound images. Biomedical Signal Processing and Control. 2024, 97: 106684. [20] Huili Zhang, Lehang Guo, Juncheng
Li, Jun Wang, Shihui Ying, Jun Shi*. Multi-view disentanglement-based bidirectional generalized
distillation for diagnosis of liver cancers with ultrasound images. Information Processing and Management.
2024,
61: 103855. [21] Xiao Wang, Xinping
Ren, Ge Jin, Shihui Ying, Jun Wang, Juncheng Li, Jun
Shi*. B-mode ultrasound-based CAD by learning using privileged information
with dual-level missing modality completion. Computers in Biology and Medicine. 2024, 182: 109106. [22] Yinghua Fu, Junfeng Liu, Jun Shi*. TSCA-Net: Transformer based spatial-channel attention
segmentation network for medical images. Computers
in Biology and Medicine. 2024, 170: 107938. [23] Jiashi Cao, Qiong Li, Huili
Zhang, Yanyan Wu, Xiang Wang, Saisai
Ding, Song Chen, Shaochun Xu, Guangwen
Duan, Defu Qiu, Jiuyi
Sun, Jun Shi*, Shiyuan Liu*. Radiomics model based on MRI to differentiate
spinal multiple myeloma from metastases: A two-center study. Journal of Bone Oncology. 2024, 45: 100599. [24] Yan Hu, Jun Wang*, Hao Zhu, Juncheng Li, Jun
Shi. Cost-sensitive weighted contrastive learning based on graph convolutional
networks for imbalanced Alzheimer’s disease staging. IEEE Transactions on Medical Imaging. 2024, 43(9): 3126-3136. [25] Lipeng Cai, Jun Shi, Shaovi Du, Yue Gao, Shihui Ying.
Self-adaptive subspace representation from a geometric intuition. Pattern Recognition. 2024, 149: 110228. [26] Bodong Cheng, Juncheng Li*, Jun Shi, Yingying Fang, Guixu Zhang, Yin Chen, Tieyong
Zeng, Zhi Li*. WeaFU: Weather-informed image blind restoration
via multi-weather distribution diffusion. IEEE
Transactions on Circuits and Systems for Video Technology. 2024, 34(12): 13530-13542. [27] Juncheng Li, Bodong Cheng, Ying Chen, Guangwei Gao, Jun
Shi, Tieyong Zeng. EWT: Efficient Wavelet-Transformer
for single image denoising. Neural
Networks. 2024, 177: 106378. [28] Yang Zhao, Bodong
Cheng, Najun Niu, Jun
Wang, Tieyong Zeng, Guixu
Zhang, Jun Shi, Juncheng Li*. Few sampling meshes-based
3D tooth segmentation via region-aware graph convolutional network. Expert Systems With
Applications. 2024, 252: 124255. [29] Juncheng Li*, Hanhui Yang, Lok Ming Lui, Guixu Zhang, Jun
Shi, Tieyong Zeng. A lightweight self-ensemble
feedback recurrent network for Fast MRI reconstruction. International Journal of Machine Learning and Cybernetics. 2024. [30] Juncheng Li, Bodong Cheng, Najun
Niu, Guangwei Gao, Shihui Ying, Jun
Shi, Tieyong Zeng. Fine-grained orthodontics
segmentation model for 3D intraoral scan data. Computers in Biology and Medicine. 2024, 168: 107821. [31] Saisai Ding, Juncheng Li, Jun Wang, Shihui Ying, Jun
Shi*. Multi-scale efficient graph-Transformer for whole slide image classification.
IEEE Journal of Biomedical and Health Informatics. 2023, 27(12): 5926-5936. [32] Ronglin Gong, Jing Shi, Jian Wang, Jun Wang, Jianwei
Zhou, Xiaofeng Lu, Jun Du*, Jun Shi*. Hybrid-supervised bidirectional
transfer networks for computer-aided diagnosis. Computers in Biology and Medicine. 2023, 65: 107409. [33] Xiangmin Han, Bangming Gong, Lehang Guo*, Jun Wang, Shihui
Ying, Shuo Li, Jun
Shi*. B-Mode ultrasound based CAD for liver cancers
via multi-view privileged information learning. Neural Networks. 2023, 164: 369-381. [34] Zhiyang Lu, Jian Wang, Zheng Li, Shihui Ying,
Jun Wang, Jun Shi*, Dinggang Shen*. Two-stage self-supervised cycle-consistency
Transformer network for reducing slice gap in MR images. IEEE Journal of Biomedical and Health Informatics. 2023, 27(7): 3337-3348. [35] Zheng Li, Shihui
Ying, Jun Wang, Hongjian He, Jun Shi*. Reconstruction of quantitative susceptibility mapping
from total field maps with local field maps guided UU-Net. IEEE Journal of Biomedical and Health Informatics. 2023, 27(4): 2047-2058. [36] Huili Zhang, Lehang Guo, Jun Wang, Shihui Ying, Jun
Shi*. Multi-view feature transformation based SVM+ for computer-aided
diagnosis of liver cancers with ultrasound images. IEEE Journal of Biomedical and Health Informatics. 2023, 27(3): 1512-1523. [37] Xiangmin Han, Jun Wang, Shihui Ying, Jun Shi*, Dinggang
Shen*. ML-DSVM+: a meta-learning based deep SVM+ for computer-aided diagnosis.
Pattern Recognition. 2023, 134:
109076. [38] Saisai Ding, Zhiyang Gao, Jun Wang, Minhua Lu*, Jun
Shi*. Fractal graph convolutional network with MLP-mixer based multi-path
feature fusion for classification of histopathological images. Expert Systems With
Applications. 2023, 212: 118793. [39] Guodong Chen, Zheng Li, Jian Wang, Jun Wang, Shisuo
Du, Jinghao Zhou, Jun Shi*, Yongkang Zhou*. An improved 3D KiU-Net for segmentation of liver tumor. Computers in Biology and Medicine.
2023, 160: 107006. [40] Jiaxin Huang#, Jun
Shi#, Saisai Ding, Huili Zhang, Xueyan Wang, Shiyang Lin, Yanfen Xu, Mingjie Wei, Longzhong Liu,
Xiaoqing Pei*. Deep learning model based on dual-modal ultrasound and
molecular data for predicting response to neoadjuvant chemotherapy in breast
cancer. Academic Radiology. 2023,
30: S50-S61. [41] Chunxiao Lai, Huili Zhang, Jing Chen, Sihui Shao, Xin Li, Minghua
Yao, Yi Zheng, Rong Wu*, Jun Shi*.
Deep learning radiomics of ultrasonography for differentiating sclerosing
adenosis from breast cancer. Clinical
Hemorheology and Microcirculation. 2023, 84: 153-163. [42] Qiong Wu, Jun Wang*, Zongqiong Sun, Lei
Xiao, Wenhao Ying, Jun Shi. Immunotherapy efficacy prediction for non-small cell
lung cancer using multi-view adaptive weighted graph convolutional networks. IEEE Journal of Biomedical and Health Informatics. 2023, 27(11): 5564-5575. [43] Hao Zhu, Jun Wang*, Yinping Zhao, Minhua
Lu, Jun Shi. Contrastive
multi-view composite graph convolutional networks based on contribution
learning for Autism Spectrum disorder
classification. IEEE Transactions on
Biomedical Engineering. 2023, 70(6): 1943 - 1954. [44] Zhaowu Lu, Jun Wang, Rui Mao, Minhua Lu, Jun Shi. Jointly composite feature
learning and Autism spectrum disorder classification
using deep multi-output Takagi-Sugeno-Kang fuzzy inference
systems. IEEE/ACM Transactions on
Computational Biology and Bioinformatics. 2023, 20(1): 476-488. [45] Xin Wang, Jun Wang, Fei Shan, Yiqiang Zhan, Jun
Shi, Dinggang Shen. Severity prediction of
pulmonary diseases using chest CT scans via cost-sensitive label multi-kernel
distribution learning. Computers in
Biology and Medicine. 2023, 159: 106890. [46] Hanhui Yang, Juncheng Li, Lok Ming Lui, Shihui Ying, Jun
Shi, Tieyong Zeng. Fast MRI reconstruction
via edge attention. Communications in
Computational Physics. 2023, 33(5): 1409-1431. [47] Jinhe Dong, Jun Shi,
Yue Gao, Shihui Ying. GAME: Gaussian mixture error
based meta learning architecture. Neural
Computing and Applications. 2023, 35: 20445-20461.
[48] Hanlin Xu, Bohan Zhang, Yaxin
Chen, Fengzhen Zeng, Wenjuan
Wang, Ziyi Chen, Ling Cao, Jun Shi, Jun Chen, Xiaoxia Zhu, Yu Xue, Rui He, Minbiao Ji, Yinghui Hua. Type
II collagen facilitates gouty arthritis by regulating MSU crystallization and
inflammatory cell recruitments. Annals
of the Rheumatic Diseases. 2023, 82(3): 416-427. [49] Xiangmin Han, Xiaoyan Fei, Jun Wang, Tao Zhou, Shihui Ying, Jun
Shi*, Dinggang Shen*. Doubly supervised transfer
classifier for computer-aided diagnosis with imbalanced modalities. IEEE Transactions on Medical Imaging.
2022, 41(8): 2009-2020. [50] Jun Wang, Fengyexin
Zhang, Xiuyi Jia, Xin Wang, Han Zhang, Shihui Ying, Qian Wang, Jun Shi*, Dinggang Shen*. Multi-class
ASD classification via label distribution learning with class-shared and class-specific
decomposition. Medical Image Analysis.
2022, 75: 102294. [51] Yanbin He, Zhiyang Lu, Jun Wang, Shihui Ying, Jun
Shi*. A self-supervised learning based channel
attention MLP-Mixer network for motor imagery decoding. IEEE Transactions on Neural Systems & Rehabilitation Engineering.
2022, 30: 2406-2417. [52] Zhiyang Lu, Jun Li, Chaoyue Wang, Rongjun Ge, Lili Chen, Hongjian
He, Jun Shi*. S2Q-Net: mining
the high-pass filtered phase data in susceptibility weighted imaging for
quantitative susceptibility mapping.
IEEE Journal of Biomedical and Health Informatics. 2022, 26(8): 3938-3949. [53] Zhiyang Gao, Zhiyang Lu, Jun Wang, Shihui Ying, Jun
Shi*. A convolutional neural network and graph convolutional network based framework for classification of breast
histopathological images. IEEE Journal of Biomedical and
Health Informatics. 2022, 26(7): 3163-3173. [54] Ronglin Gong, Xiangmin Han, Jun Wang, Shihui Ying, Jun
Shi*. Self-supervised bi-channel Transformer networks for computer-aided
diagnosis. IEEE Journal of Biomedical and
Health Informatics. 2022, 26(7): 3435-3446. [55] Bangming Gong, Jing Shi, Xiangmin Han, Huan
Zhang, Yuemin Huang, Liwei Hu, Jun Wang, Jun Du*, Jun Shi*. Diagnosis of
infantile hip dysplasia with B-mode ultrasound via two-stage meta-learning
based deep exclusivity regularized machine. IEEE Journal of Biomedical and Health Informatics. 2022, 26(1):
334-344. [56] Ronglin Gong, Linlin Wang, Jun Wang, Binjie Ge, Hang Yu, Jun
Shi*. Self-distilled supervised contrastive learning for diagnosis of
breast cancers with histopathological images. Computers in Biology and Medicine. 2022, 146:105641. [57] Weijie Kang, Min Ji, Huili Zhang, Hua Shi, Tianchao Xiang, Yaqi Li, Ye Fang,
Qi Qi, Junbo Wang, Jian
Shen, Liangfeng Tang, Xiaoxiong
Liu, Yingzi Ye, Xiaoling
Ge, Xiang Wang, Hong Xu, Zhongwei Qiao*, Jun Shi*,
Jia Rao*. A novel clinical-radiomics model predicted renal lesions and
deficiency in children on diffusion-weighted MRI. Frontiers in Physics. 2022. [58] Jun Wang, Zhuangzhuang
Zhao, Zhaohong Deng, Kup-Sze
Choi, Lejun Gong, Jun Shi, Shitong Wang.
Manifold-regularized multitask fuzzy system modeling with low-rank and sparse
structures in consequent parameters. IEEE
Transactions on Fuzzy Systems. 2022, 30(5): 1486-1500. [59] Weichang Ding, Jun Wang, Weijun Zhou, Shichong Zhou, Cai Chang, Jun Shi. Joint localization and classification of breast cancer
in B-mode ultrasound imaging via collaborative learning with elastography. IEEE Journal of Biomedical and Health
Informatics. 2022, 26(9): 4474-4485. [60] Xing Wu*, Cheng Chen, Mingyu
Zhong, Jianjia Wang, Jun Shi*. COVID-AL: the diagnosis of COVID-19 with deep
active learning. Medical Image Analysis.
2021, 63: 101913. [61] Xiaoyan Fei, Shichong Zhou, Xiangmin Han, Jun Wang, Shihui
Ying, Cai Chang, Weijun Zhou, Jun Shi*. Doubly supervised parameter transfer classifier
for diagnosis of breast cancer with imbalanced ultrasound imaging modalities.
Pattern Recognition. 2021, 120:
108139. [62] Huili Zhang, Lehang Guo, Dan Wang, Jun Wang,
Lili Bao, Shihui Ying, Huixiong
Xu*, Jun Shi*. Multi-source
transfer learning via multi-kernel support vector machine plus for B-mode
ultrasound-based computer-aided diagnosis of liver cancers. IEEE Journal of Biomedical and Health
Informatics. 2021, 25(10): 3874-3885. [63] Zheng Li, Jun Li, Chaoyue Wang, Zhiyang Lu, Jun Wang,
Hongjian He*, Jun Shi*. Meta-learning based interactively connected clique U-Net for quantitative
susceptibility mapping. IEEE
Transactions on Computational Imaging. 2021, 7: 1385-1399. [64] Zheng Li, Chaofeng
Wang, Jun Wang, Shihui Ying, Jun Shi*. Lightweight adaptive weighted network for single
image super-resolution. Computer Vision
and Image Understanding. 2021, 211: 103254. [65] Shanshan Wang#, Guohua Cao#, Yan Wang#, Shu Liao#, Qian Wang#, Jun Shi#, Cheng Li, Dinggang Shen*. Review and prospect: artificial intelligence
in advanced medical imaging. Frontiers
in Radiology. 2021, 1: 781868. [66] Weiwen Wu, Jun Shi, Hengyong Yu, Weifei Wu*, Varut Vardhanabhuti*. Tensor gradient
L0-norm minimization based low-dose CT and its application to COVID-19. IEEE Transactions on Instrumentation &
Measurement. 2021, 70: 4503012. [67] Jun Wang, Lichi Zhang, Qian
Wang*, Lei Chen, Jun Shi,
Xiaobo Chen, Zuoyong Li, Dinggang
Shen*. Multi-class ASD classification based on functional connectivity and
functional correlation tensor via multi-source domain adaptation and
multi-view sparse representation. IEEE
Transactions on Medical Imaging. 2020, 39(10): 3137-3147. [68] Xiaoyan Fei, Jun Wang, Shihui Ying, Zhongyi Hu, Jun
Shi*. Projective parameter transfer based sparse multiple empirical
kernel learning machine for diagnosis of brain disease. Neurocomputing. 2020, 413: 271-283. [69] Xiaoyan Fei, Lu Shen, Shihui Ying, Yehua Cai, Qi Zhang, Wentao
Kong, Weijun Zhou, Jun Shi*. Parameter transfer deep neural network for
single-modal B-mode ultrasound-based computer aided diagnosis. Cognitive Computation. 2020, 12:
1252-1264. [70] Lu
Shen, Jun Shi*, Yun Dong, Shihui Ying, Yaxin Peng, Lu
Chen, Qi Zhang, Hedi An, Yingchun
Zhang. An improved deep polynomial network algorithm for transcranial sonography based diagnosis of Parkinson’s disease. Cognitive Computation. 2020, 12: 553-562. [71] Jun Shi, Zeyu
Xue, Yakang Dai, Bo Peng, Yun Dong, Qi Zhang, Yingchun Zhang. Cascaded multi-column RVFL+ classifier
for single-modal neuroimaging-based diagnosis of Parkinson’s disease. IEEE Transactions on Biomedical
Engineering. 2019, 66(8): 2362-2371. [72] Jun Shi, Xiao Zheng, Jinjie Wu, Yan Li, Qi Zhang, Shihui
Ying. Quaternion Grassmann average network for learning
representation of histopathological image. Pattern Recognition. 2019, 89: 67-76. [73] Jun Shi, Zheng Li, Shihui
Ying, Chaofeng Wang, Qi Zhang, Pingkun
Yan. MR image super-resolution via wide residual networks with fixed skip
connection. IEEE Journal of Biomedical
and Health Informatics. 2019, 23(3): 1129-1140. [74] Yan Li, Fanqing
Meng, Jun Shi*. Learning
using privileged information improves neuroimaging-based CAD of Alzheimer's
disease: a comparative study. Medical
& Biological Engineering & Computing. 2019, 57(7): 1605-1616. [75] Xiaoyan Fei, Yun Dong, Hedi An, Qi Zhang, Yingchun Zhang, Jun
Shi*. Impact of region of interest size on transcranial sonography based computer-aided diagnosis for Parkinson’s
disease. Mathematical Biosciences and
Engineering. 2019, 16(5): 5640-5651. [76] Qi Zhang, Shuang Song, Yang
Xiao, Shuai Chen, Jun Shi, Hairong Zheng. Dual-modal artificially intelligent
diagnosis of breast tumors on both shear-wave elastography and B-mode
ultrasound using deep polynomial networks. Medical Engineering and Physics, 2019, 64: 1-6. [77] Bangming Gong, Jun Shi*,
Shihui Ying, Yakang Dai,
Qi Zhang, Yun Dong, Hedi An, Yingchun
Zhang. Neuroimaging-based diagnosis of Parkinson’s disease with deep neural
mapping large margin distribution machine. Neurocomputing. 2018, 320: 141-149. [78] Jun Shi, Qingping
Liu, Chaofeng Wang, Qi Zhang, Shihui
Ying, Haoyu Xu. Super-resolution reconstruction of
MR image with a novel residual learning network algorithm. Physics in Medicine & Biology.
2018, 63(8):085011. [79] Lehang Guo, Dan Wang, Yiyi Qian, Xiao Zheng, Chongke
Zhao, Xiaolong Li, Xiaowan
Bo, Wenwen Yue, Qi Zhang, Jun Shi*, Huixiong Xu. A two-stage
multi-view learning framework based computer-aided diagnosis
of liver tumors with contrast enhanced ultrasound images. Clinical Hemorheology and Microcirculation.
2018, 69(3): 343-354. [80] Shihui Ying, Zhijie Wen, Jun Shi, Yaxin Peng, Jigen Peng, Hong Qiao. Manifold
preserving: an intrinsic approach for semi-supervised distance metric learning.
IEEE Transactions on Neural Networks
and Learning Systems. 2018, 29(7): 2731-2742. [81] Qi Zhang, Yue Liu, Hong Han, Jun Shi, Wenping
Wang. Artificial intelligence based diagnosis for
cervical lymph node malignancy using the point-wise gated Boltzmann machine. IEEE Access. 2018, 6: 60605 - 60612. [82] Meihui Qiu, Huifeng
Zhang, David Mellor, Jun Shi,
Chuangxin Wu, Yueqi
Huang, Jianye Zhang, Ting Shen, Daihui
Peng. Aberrant neural activity in patients with bipolar depressive disorder
distinguishing to the unipolar depressive disorder: a resting-state
functional magnetic resonance imaging study. Frontiers in Psychiatry. 2018, 9: 238. [83] Jun Shi, Jinjie
Wu, Yan Li, Qi Zhang, Shihui Ying. Histopathological
image classification with color pattern random binary hashing based PCANet and matrix-form classifier. IEEE Journal of Biomedical and Health Informatics. 2017, 21(5):
1327-1337. [84] Junjie
Zhang, Jie Yin, Qi Zhang, Jun Shi*, Yan Li. Robust sound event classification with bilinear multi-column
ELM-AE and two-stage ensemble learning. EURASIP
Journal on Audio, Speech, and Music Processing. 2017, 11. [85] Huaipeng Dong, Qi Zhang, Jun
Shi. Intensity inhomogeneity compensation and tissue segmentation for
magnetic resonance imaging with noise-suppressed multiplicative intrinsic
component optimization. Optical
Engineering. 2017, 56(12): 123103. [86] Qi Zhang, Jing Yao, Yehua Cai, Limin Zhang, Yishuo Wu, Jingyu Xiong, Jun Shi, Yuanyuan Wang, Yi
Wang. Elevated hardness of peripheral gland on real-time elastography is an
independent marker for high-risk prostate cancers. La Radiologia Medica. 2017, 122(12):
944-951. [87] Qi Zhang, Yang Xiao, Jingfeng Suo, Jun
Shi, Jinhua Yu, Yi Guo, Yuanyuan Wang, Hairong Zheng. Sonoelastomics
for breast tumor classification: a radiomics approach with clustering-based
feature selection on sonoelastography. Ultrasound in Medicine and Biology.
2017, 43(5): 1058-1069. [88] Qi Zhang, Jingfeng
Suo, Wanying Chang, Jun Shi, Man Chen. Dual-modal computer-assisted evaluation
of axillary lymph node metastasis in breast cancer patients on both real-time
elastography and B-mode ultrasound. European
Journal of Radiology, 2017, 95, 66-74. [89] Qi Zhang, Congcong
Yuan, Wei Dai, Lei Tang, Jun Shi,
Zuoyong Li, Man Chen. Evaluating pathologic
response of breast cancer to neoadjuvant chemotherapy with computer-extracted
features from contrast-enhanced ultrasound videos. Physica Medica, 2017, 39, 156-163. [90] Qi Zhang, Yehua
Cai, Yinghui Hua, Jun Shi, Yuanyuan Wang, Yi Wang. Sonoelastography
shows that Achilles tendons with insertional tendinopathy are harder than
asymptomatic tendons. Knee Surgery,
Sports Traumatology, Arthroscopy. 2017, 25: 1839-1848. [91] Jun Shi, Shichong
Zhou, Xiao Liu, Qi Zhang, Minhua Lu, Tianfu Wang. Stacked
deep polynomial network based representation learning
for tumor classification with small ultrasound image dataset. Neurocomputing. 2016, 194: 87-94. [92] Qi Zhang, Yang Xiao, Wei Dai, Jingfeng Suo, Congzhi Wang, Jun Shi, Hairong
Zheng. Deep learning based classification of breast
tumors with shear-wave elastography. Ultrasonics.
2016, 72: 150-157. [93] Jun Shi, Xiao Liu, Yan Li, Qi Zhang,
Yingjie Li, Shihui Ying. Multi-channel EEG based
sleep stage classification with joint collaborative representation and
multiple kernel learning. Journal of Neuroscience
Methods. 2015, 254: 94-101. [94] Jun Shi, Qikun
Jiang, Qi Zhang, Qinghua Huang, Xuelong
Li. Sparse kernel entropy component analysis for dimensionality reduction of biomedical
data. Neurocomputing. 2015, 168:
930-940. [95] Jun Shi, Qikun
Jiang, Rui Mao, Minhua Lu, Tianfu Wang. FR-KECA: fuzzy
robust kernel entropy component analysis.
Neurocomputing. 2015, 149: 1415-1423. [96] Jun Shi, Yi Li, Jie Zhu, Haojie Sun, Yin Cai. Joint sparse coding based spatial pyramid
matching for classification of color medical image. Computerized Medical Imaging and Graphics. 2015, 41: 61-66. [97] Qi Zhang, Chaolun
Li, Hong Han, Wei Dai, Jun Shi,
Yuanyuan Wang, Wenping Wang.
Spatiotemporal quantification of carotid plaque neovascularization on
contrast-enhanced ultrasound: correlation with visual grading and
histopathology. European Journal of
Vascular and Endovascular Surgery. 2015, 50(3): 289-296. [98] Qi Zhang, Chaolun
Li, Moli Zhou, Yu Liao, Chunchun
Huang, Jun Shi, Yuanyuan
Wang, Wenping Wang. Quantification of carotid
plaque elasticity and intraplaque neovascularization using contrast-enhanced
ultrasound and imager egistration-based
elastography. Ultrasonics. 2015, 62:
253-262. [99] Huali Chang, Zhenping Chen, Qinghua Huang, Jun
Shi, Xuelong Li. Graph-based learning for segmentation
of 3D ultrasound images. Neurocomputing.
2015, 151: 632-644. [100] Jun Shi, Yin Cai, Jie Zhu, Jin Zhong,
Fei Wang. SEMG-based hand motion recognition using cumulative residual entropy
and extreme learning machine. Medical
& Biological Engineering & Computing. 2013, 51(4): 417-427. [101] Shichong Zhou, Jun Shi*,
Jie Zhu, Yin Cai, Ruiling Wang. Shearlet-based
texture feature extraction for classification of breast tumor in ultrasound image.
Biomedical Signal Processing and
Control. 2013, 8(6): 688-696. [102] Jun Shi, Jingyi Guo, Shuxian Hu, Yongping Zheng. Recognition of finger flexion
motion from ultrasound image: a feasibility study. Ultrasound in Medicine and Biology. 2012, 38(10): 1695-1704. [103] Jun Shi, Qian Chang, Yongping Zheng.
Feasibility of controlling a prosthetic hand using sonomyography
signal in real time: a preliminary study. Journal
of Rehabilitation Research and Development. 2010, 47(2): 87-98. [104] Jiehui Jiang, Zhuangzhi Yan, Jun Shi, et al. A mobile
monitoring system of blood pressure for underserved in China by information
and communication technology service. IEEE
Transactions on Information Technology in Biomedicine. 2010, 14(3):
748-757. [105] Xin Chen, Yongping Zheng, Jingyi
Guo, Jun Shi. Sonomyography (SMG) Control for Powered Prosthetic Hand:
A Study with Normal Subjects. Ultrasound
in Medicine and Biology. 2010, 36(7): 1076-1088. [106] Jun Shi, Yongping Zheng, Xin Chen, Hongbo Xie. Modeling the relationship between wrist angle
and muscle thickness during wrist flexion-extension based on the bone-muscle
lever system: a comparison study. Medical
Engineering and Physics. 2009, 31(10): 1125-1160. [107] Hongbo Xie, Yongping Zheng, Jingyi Guo, Xin Chen, Jun Shi. Estimation of wrist angle from sonomyography using support vector machine and artificial
neural network models. Medical
Engineering and Physics. 2009, 31(3): 384-391. [108] Jun Shi, Yongping Zheng, Qinghua Huang, Xin Chen. Continuous monitoring of sonomyography, electromyography and torque generated by
normal upper arm muscles during isometric contraction: sonomyography
assessment for arm muscles. IEEE
Transactions on Biomedical Engineering. 2008, 55(3): 1191-1198. [109] Jun Shi, Yongping Zheng, Xin Chen, et al. Assessment of muscle fatigue using sonomyography:
muscle thickness change detected from ultrasound images. Medical Engineering and Physics. 2007, 29(4): 472-479. [110] Yongping Zheng, Matthew Chan, Jun Shi, et al. Sonomyography: monitoring morphological changes of
forearm muscles in actions with the feasibility for the control of powered
prosthesis. Medical Engineering and
Physics. 2006, 28: 405-415. [111] Yongping Zheng, Jun Shi, et al. Dynamic
Depth-dependent Osmotic Swelling and Solute Diffusion in Articular Cartilage
Monitored using Real-time Ultrasound.
Ultrasound in Medicine and Biology. 2004, 30 (6): 841-849. [112] Yongping Zheng, SL Bridal, Jun Shi, et al. High resolution ultrasound elastomicroscopy
imaging of soft tissues: System development and feasibility. Physics in Medicine and Biology. 2004,
49(17): 3925-3938. Selected Conference Publications: [1] Ke
Sun, Jing Shi, Jun Du, Qian Wang, Jun
Shi*. Hybrid symmetry Mamba network for ultrasound-based CAD of developmental
dysplasia of the Hip. The 47th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBC). 2025. [2] Tianxiang Huang, Jing Shi, Ge Jin, Juncheng Li, Jun
Wang, Jun Du*, Jun Shi*. Topological
GCN for improving detection of hip landmarks from B-mode ultrasound Images. The 27th International Conference on
Medical Image Computing and Computer Assisted Intervention (MICCAI). 2024 (Oral presentation, 2.7%). [3] Saisai Ding, Jun Wang, Juncheng Li, Jun Shi*. Multi-scale prototypical
Transformer for whole slide image classification. The 26th International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI). 2023. [4] Yanbin He, Zhiyang Lu, Jun Wang, Jun Shi*. A channel attention
based MLP-Mixer network for motor imagery decoding with EEG. 2022 IEEE International Conference on
Acoustics, Speech and Signal Processing (ICASSP). 2022. [5] Ronglin Gong, Shihui Ying, and Jun Shi*. Task-driven self-supervised
bi-channel networks learning for diagnosis of breast cancers with mammography.
2022 IEEE International Conference in
Image Processing (ICIP). 2022. [6] Zhiyang Gao, Jun Wang, Jun
Shi*. GQ-GCN: Group quadratic graph convolution network for classification
of histopathological images. The 24th
International Conference on Medical Image Computing and Computer Assisted
Intervention (MICCAI). 2021. [7] Zhiyang Lu, Zheng Li, Jun Wang, Jun
Shi*, Dinggang Shen*. Two-stage self-supervised cycle-consistency network for reconstruction
of thin-slice MR images. The 24th International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI). 2021. [8] Zhiyang Lu, Jun Li, Zheng Li, Hongjian He, Jun Shi*. Reconstruction of
quantitative susceptibility maps from phase of susceptibility weighted
imaging with cross-connected Ψ-Net. The
2021 IEEE International Symposium on
Biomedical Imaging (ISBI). 2021. [9] Xiangmin Han, Jun Wang, Weijun Zhou, Cai Chang,
Shihui Ying, Jun
Shi*. Deep doubly supervised transfer network for diagnosis of breast
cancer with imbalanced ultrasound imaging modalities. The 23rd International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI). 2020. [10] Bangming Gong, Lu Shen, Cai Chang, Shichong
Zhou, Weijun Zhou, Shuo
Li, Jun Shi*. Bi-modal ultrasound breast cancer diagnosis via multi-view deep
neural network SVM. IEEE International
Symposium on Biomedical Imaging (ISBI). 2020. [11] Zheng Li, Qingping
Liu, Yiran Li, Qiu Ge, Yuanqi
Shang, Donghui Song, Ze Wang*, Jun Shi*. A two-stage multi-loss super-resolution network for
arterial spin labeling magnetic resonance imaging. The 22nd International Conference on Medical Image Computing and
Computer Assisted Intervention (MICCAI). 2019. (Graduate
Student Travel Award) [12] Jun Wang, Ying Zhang, Tao Zhou,
Zhaohong Deng, Huifang Huang, Shitong
Wang, Jun Shi, Dinggang Shen. Interpretable feature learning using multi-output
Takagi-Sugeno-Kang fuzzy system for multi-center
ASD diagnosis. The 22nd International
Conference on Medical Image Computing and Computer Assisted Intervention
(MICCAI). 2019. [13] Xiaoyan Fei, Weijun Zhou, Lu Shen, Cai Chang, Wentao Kong, Shichong Zhou, Jun Shi*, Ultrasound-based diagnosis
of breast tumor with parameter transfer multilayer kernel extreme learning machine.
The 41st Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS).
2019. [14] Jun Shi, Minjun
Yan, Yun Dong, Xiao Zheng, Qi Zhang, Hedi An. Multiple kernel
learning based classification of Parkinson’s disease with multi-modal
transcranial sonography. The 40th
Annual International Conference of the IEEE Engineering in Medicine and
Biology Society (EMBS). 2018. (Oral Representation) [15] Lu Shen, Jun Shi*, Bangming Gong, Yingchun Zhang, Yun Dong, Qi Zhang, Hedi An. Multiple empirical kernel mapping based broad
learning system for classification of Parkinson’s disease with transcranial sonography. The 40th Annual
International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBS). 2018. (Oral Representation) [16] Fanqing Meng, Jun Shi*, Bangming Gong, Qi Zhang, Lehang
Guo, Dan Wang, Huixiong Xu*. B-mode ultrasound based diagnosis of liver cancer with CEUS images
as privileged information. The 40th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBS). 2018. (Oral Representation) [17] Zeyu Xue, Jun Shi*, Yakang Dai, Yun Dong, Qi Zhang, Yingchun
Zhang. Transcranial sonography based diagnosis of
Parkinson’s disease via cascaded kernel RVFL+. The 40th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBS). 2018. [18] Haohao Xu, Qi Zhang, Huaipeng
Dong, Xiyuan Jiang, Jun Shi. Suppression of ultrasonography using maximum
likelihood estimation and weighted nuclear norm minimization. The 40th Annual
International Conference of the IEEE Engineering in Medicine and Biology
Society (EMBS). 2018. [19] Qingping Liu, Jun Shi*, Ze Wang. Reconstructing high-resolution arterial spin labeling perfusion
images via convolutional neural networks residual-learning based methods. Joint Annual Meeting ISMRM-ESMRMB.
2018. [20] Xiao
Zheng, Jun Shi*, Qi Zhang, Shihui Ying, Yan Li. Improving
MRI-based diagnosis of Alzheimer’s disease via an ensemble privileged
information learning algorithm. 2017 IEEE International Symposium on Biomedical Imaging
(ISBI). 2017. (Oral Representation) [21] Chaofeng
Wang, Jun Shi*, Qi Zhang, Shihui
Ying. Histopathological image classification with bilinear convolutional
neural networks. The 39th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [22] Yiyi
Qian, Jun Shi*, Xiao Zheng, Qi Zhang, Lehang Guo, Dan
Wang, Huixiong Xu. Multimodal ultrasound imaging based diagnosis of liver cancers with a two-stage
multi-view learning framework. The 39th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [23] Lehang Guo, Dan Wang, Huixiong Xu, Yiyi Qian,
Chaofeng Wang, Xiao Zheng, Qi Zhang, Jun Shi*. CEUS-based classification of
liver tumors with deep canonical correlation analysis and
multi-kernel learning. The 39th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBS). 2017. (Oral Representation) [24] Jinjie Wu, Jun Shi*, Yan Li, Jingfeng
Suo, Qi Zhang. Histopathological image classification using random binary hashing
based PCANet and bilinear classifier. The 2016 European Signal Processing
Conference (EUSIPCO). 2016. (Oral Representation) [25] Xiao
Zheng, Jun Shi*, Yan Li, Xiao Liu, Qi Zhang. Multi-modality stacked deep
polynomial network based feature learning for
Alzheimer’s disease diagnosis. 2016 IEEE International Symposium on Biomedical Imaging
(ISBI). 2016. [26] Xiao
Zheng, Jun Shi*, Shihui
Ying, Qi Zhang, Yan Li. Improving single-modal neuroimaging based
diagnosis of brain disorders via boosted privileged information learning framework.
2016 MICCAI Workshop on Machine Learning in Medical
Imaging (MLMI).
2016. [27] Jinjie Wu, Jun Shi*, Shihui
Ying, Qi Zhang, Yan Li. Learning representation for histopathological image with quaternion
Grassmann average network. 2016
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI). 2016. [28] Xiao Liu, Jun Shi*, Qi Zhang. Tumor classification by deep polynomial network and
multiple kernel learning on small ultrasound image dataset. 2015
MICCAI Workshop on Machine Learning in Medical Imaging (MLMI). 2015. [29] Jie Zhu, Jun Shi*. Hessian regularization based semi-supervised dimensionality
reduction for neuroimaging data of Alzheimer’s disease. 2014 IEEE International Symposium on Biomedical Imaging (ISBI).
2014. [30] Xiao Liu, Jun Shi*, Shichong Zhou, Minhua Lu. An iterated Laplacian based semi-supervised dimensionality
reduction for classification of breast cancer on ultrasound images. The 36th Annual International Conference of the IEEE Engineering
in Medicine and Biology Society (EMBS).
2014. [31] Qikun Jiang, Jun Shi*.
Sparse kernel entropy component analysis for dimensionality reduction of neuroimaging
data. The 36th Annual International
Conference of the IEEE Engineering in Medicine and Biology Society (EMBS). 2014. [32] Jun Shi,
Yin Cai. Joint sparse
coding spatial pyramid matching for classification of color blood cell image.
2013 MICCAI Workshop on Machine
Learning in Medical Imaging (MLMI). 2013. |