(1)   发表相关学术论文

SCI/EI检索期刊论文:

1. [1] Yang Li, Qiannan Shen, Mingfeng Jiang*, Lingyan Zhu, Yongming Li, Pin Wang and Tie-Qiang Li. Accelerating Dynamic MRI Reconstruction Using Adaptive Sequentially Truncated Higher-Order Singular Value Decomposition[J]. Current Medical Imaging, 2022, 18, 719-730.

2. [2] Yuni Zeng, Hang Lv, Mingfeng Jiang*, Jucheng Zhang, Ling Xia, Yaming Wang and Zhikang Wang.  Deep arrhythmia classification based on SENet and lightweight context transform[J]. Mathematical Biosciences and Engineering，2022，20(1):1-17.

3. [3] Xian Fang∗, Mingfeng Jiang, Jinchao Zhu , Xiuli Shao , Hongpeng Wang. M2RNet: Multi-modal and multi-scale refined network for RGB-D salient object detection[J].  Pattern Recognition，2023，135: 109139.

4. [4] Bin Yan, Yang Li, Lin Li, Xiaocheng Yang, Tie-qiang Li, Guang Yang, Mingfeng Jiang* . Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer’s disease classification[J]. Computers in Biology and Medicine, 2022, 148 :105944.

5. [5] Mingfeng Jiang* , Yujie Qiu, Wei Zhang, Jucheng Zhang, Zhefeng Wang, Wei Ke, Yongquan Wu, Zhikang Wang.Visualization deep learning model for automatic arrhythmias classification[J]. Physiological Measurement, 2022, 43:085003.

6. [6] Jucheng Zhang, Lulu Han, Jianzhong Sun, Zhikang Wang, Wenlong Xu, Yonghua Chu, Ling Xia and Mingfeng Jiang*. Compressed sensing based dynamic MR image reconstruction by using 3D total generalized variation and tensor decomposition: k-t TGV-TD [J]. BMC Medical Imaging , 2022, 22:101.

7. [7] Mingfeng Jiang, Bin Yan , Yang Li*, Jucheng Zhang , Tieqiang Li, Wei Ke. Image Classification of Alzheimer’s Disease Based on External-Attention Mechanism and Fully Convolutional Network[J]. Brain Sciences, 2022, 12, 319.

8. [8] Mingfeng Jiang*, Minghao Zhi, Liying Wei, Xiaocheng Yang, Jucheng Zhang, Yongming Li, Pin Wang, Jiahao Huang, Guang Yang*.  FA-GAN: Fused attentive generative adversarial networks for MRI image super-resolution[J]. Computerized Medical Imaging and Graphics, 2021, 92: 101969

9. [9] Mingfeng Jiang*, Jiayan Gu, Yang Li, Bo Wei, Jucheng Zhang, Zhikang Wang* and Ling Xia. HADLN: Hybrid Attention-Based Deep Learning Network for Automated Arrhythmia Classification[J]. Frontiers in Physiology, 2021, 12:683025. doi: 10.3389/fphys.2021.683025

10. [10] Yi Lu, Mingfeng Jiang*, Liying Wei, Jucheng Zhang, Zhikang Wang, Bo Wei, Ling Xia.  Automated arrhythmia classification using depthwise separable convolutional neural network with focal loss[J]. Biomedical Signal Processing and Control，2021，69 : 102843.  3.137

11. [11] 蒋明峰, 支明豪, 李杨, 李铁强，张鞠成. 基于自注意力机制生成对抗网络的超分辨率磁共振图像重建[J]. 中国科学: 信息科学, 2021, 51(6): 959-970.

12. [12] Yongming Li*, Yan Lei, Pin Wang, Mingfeng Jiang, Yuchuan Liu. Hybrid Embedded Deep Stacked Sparse Autoencoder with w_LPPD SVM Ensemble[J]. Applied Soft Computing, 2021, 101:107003.  5.472

13. [13] Pin Wang*, Jiaxin Wang, Yongming Li, Pufei Li, Linyu Li, Mingfeng Jiang. Automatic classification of breast cancer histopathological images based on deep feature fusion and enhanced routing[J]. Biomedical Signal Processing and Control, 2021, 65:102341.  3.137

14. [14] Xu Yang, Pengfei Jiang , Mingfeng Jiang , Lu Xu , Long Wu* , Chenghua Yang, Wei Zhang, Jianlong Zhang , Yong Zhang*.  High imaging quality of Fourier single pixel imaging based on generative adversarial networks at low sampling rate[J]. Optics and Lasers in Engineering, 2021, 140:106.  4.273

15. [15] Bo Wei, Xuan Wang, Xuewen Xia, Mingfeng Jiang, Zuohua Ding, Yanrong Huang. Novel self-adjusted particle swarm optimization algorithm for feature selection[J]. Computing, 2021, https://doi.org/10.1007/ s00607-020-00891-w. 

16. [16] Xiaocheng Yang,* Zhenyi Yang, Jingye Yan, Lin Wu, Mingfeng Jiang. Multi-Parameter Regularization Method for Synthetic Aperture Imaging Radiometers. Remote Sensing, 2021, 13:382. https://doi.org/10.3390/rs13030382. 

17. [17] Yongming Li, Fan Li, Yuanlin Zheng, Pin Wang, Mingfeng Jiang, & Xinke Li  Hierarchical age estimation mechanism with adaBoost-based deep instance weighted fusion[J].  Journal of Experimental & Theoretical Artificial Intelligence, 2020, DOI:10.1080/0952813X.2020.1764633  

18. [18] Zhenmou Yuan, Mingfeng Jiang*, Yaming Wang, Bo Wei, Yongming Li, Pin Wang, Wade Menpes-Smith, Zhangming Niu and Guang Yang. SARA-GAN: Self-Attention and Relative Average Discriminator Based Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction[J]. Frontiers in Neuroinformatics, 2020, 14: 611666. doi: 10.3389/ fninf.2020.611666 

19. [19] Xu Yang, Lu Xu, Mingfeng Jiang, Long Wu, Yuehao Liu, Yong Zhang, Phase-coded modulation 3D ghost imaging[J]. Optik, 2020, 220: 165184.  

20. [20] Xiaocheng Yang, Zhenyi  Yang，Jingye Yan， Lin Wu, Mingfeng Jiang,  Wentao Lyu. Reduction of the Reconstruction Error With Lower and Upper Bounds in Synthetic Aperture Imaging Radiometers[J]. IEEE ACCESS, 2020, 8: 156964-156971.

21. [21] 蒋明峰*，鲁薏，李杨，项宜坤，张鞠成，王志康. 基于金字塔卷积结构的深度残差网络心电信号分类方法研究[J]. 生物医学工程学杂志，2020, Vol. 37 (4): 692-698.

22. [22] 袁子晗，蒋明峰*，李杨，支明豪，朱志军. 基于DAWGAN-GP的磁共振图像重构方法研究[J]. 电子学报，2020, Vol. 48 (10): 1883-1890.

23. [23] Mingfeng Jiang*, Qiannan Shen, Yang Li, Xiaocheng Yang, Jucheng Zhang, Yaming Wang, Ling Xia. Improved robust tensor principal component analysis for accelerating dynamic MR imaging reconstruction[J]. Medical & Biological Engineering & Computing，2020，58:1483–1498   2.039

24. [24] Mingfeng Jiang*, Zihan Yuan, Xu Yang, Jucheng Zhang, Yinglan Gong, Tieqiang Li. Accelerating CS-MRI Reconstruction With Fine-Tuning Wasserstein Generative Adversarial Network[J]. IEEE ACCESS, 2019, 7: 152348-152357.   4.089

25. [25] Mingfeng Jiang*, Liang Lu, Yi Shen, Long Wu, Yinglan Gong, Ling Xia, Feng Liu. Directional tensor product complex tight framelets for compressed sensing MRI reconstruction[J]. IET Image Processing, 2019, 13(12): 2183-2189. 2.004

26. [26] 蒋明峰*，陆亮，吴龙，徐文龙，汪亚明. 基于加权Schatten P范数最小化的磁共振图像重构方法研究[J]. 电子学报，2019, Vol. 47 (4): 784-790.

27. [27] Hongjuan Yu, Mingfeng Jiang*, Hairong Chen, Jie Feng, Yaming Wang, Yu Lu. Super-pixel algorithm and group sparsity regularization method for compressed sensing MR image reconstruction[J]. Optik, 2017, 140 , 392-404.

28. [28] 蒋明峰*，陆雨，朱志军，徐文龙，汪亚明.基于多尺度低秩模型的心脏磁共振成像方法研究[J]. 电子学报，2017, Vol. 45 (9): 2128-2134.

29. [29] Mingfeng Jiang*, Yuan Liu, Wenlong  Xu, Jie Hu, Yaming Wang, Yinglan Gong, and Ling Xia. Efficient Compressed Sensing Reconstruction Using Group Sparse Total Variation Regularization[J]. Journal of Medical Imaging and Health Informatics, 2015, Vol. 5: 907–917.

30. [30] Yaming Wang*, Lingling. Tong, Mingfeng Jiang, Junbao Zheng. Non-Rigid Structure Estimation in Trajectory Space from Monocular Vision[J]. Sensors, 2015, 15: 25730-25745.

31. [31] Mingfeng Jiang*, Heng Zhang, Lingyan Zhu, Li Cao, Yaming Wang, Ling Xia, Yinglan Gong. Noninvasive reconstruction of cardiac transmembrane potentials using kernelized extreme learning method[J]. Physics in Medicine and Biology, 2015, 60, 3237-3253.

32. [32] 蒋明峰*，刘渊，徐文龙，冯杰，汪亚明. 基于全变分扩展方法的压缩感知磁共振成像算法研究[J]. 电子与信息学报, 2015, 37(11): 2608-2612.

33. [33] Zeng Feng, Feng Liu*, Mingfeng Jiang, Stuart Crozier, He Guo, Yuxin Wang. Improved l1-SPIRiT using 3D walsh transform-based sparsity basis [J]. Magnetic Resonance Imaging, 2014, 32:924-933.

34. [34] 蒋明峰*, 朱礼涛, 汪亚明, 夏灵, 龚莹岚. 结合非线性GRAPPA与SENSE的并行磁共振成像研究[J]. 浙江大学学报(工学版), 2014, 48(10):1865-1870.

35. [35] Mingfeng Jiang, Jin Jin, Feng Liu*, Yeyang Yu, Ling Xia, Yaming Wang, Stuart Crozie. Sparsity-constrained SENSE reconstruction: An efficient implementation using a fast composite splitting algorithm[J]. Magnetic Resonance Imaging 31:1218–1227, 2013.

36. [36] Mingfeng Jiang*, Yaming Wang, Ling Xia, Feng Liu, Shanshan Jiang, Wenqing Huang, “The combination of self-organizing feature maps and supportvector regression for solving the inverse ECG problem[J]. Computers and Mathematics with Applications, 66:1981–1990, 2013.

(2)主持及参与科研项目

[1]  面向房颤复发预测的心脏磁共振影像智能处理与分析方法研究 ，62272415,国家自然科学基金面上项目，54万元，2023.01-2026.12，主持。

[2] 快速高分辨率磁共振成像及其脑类淋巴系统中的应用, 62011530130，国家自然科学基金委国际合作与交流项目，40万元，2020.07-2023.06，主持。

[3] 基于张量低秩稀疏分解与运动校正的动态心脏磁共振快速成像方法研究，61672466，国家自然科学基金面上项目，75万元，2017.01-2020.12，主持。

[4] 基于支持向量回归的心脏电功能成像反演问题研究，30900322，国家自然科学基金青年基金项目，20万元，2010.01-2012.12，主持。

[5] 智慧医疗设备与系统研发-基于可解释性卷积循环神经网络的心律失常智能监测平台研究，2020C03060，浙江省科技厅重点研发项目，2020.01-2022.12， 110万/250万元，参与（高校主持人）。

[6]  基于生成式对抗网络和迁移学习的心脏磁共振图像智能重构方法研究， LSZ19F010001, 浙江省基金-数理医学学会联合基金重点项目，35万元， 2019.01-2022.12，主持。

[7] 基于张量低秩稀疏分解的动态磁共振快速成像关键技术研究, 2015C31075， 浙江省科技厅公益项目，15万元，2015.07-2017.07，主持。

[8]基于径向采样轨迹和稀疏约束的三维心脏磁共振成像技术研究, LY14F010022，浙江省自然科学基金，9万元，2014.01-2016.12，主持。

[9] 基于支持向量机的心脏电生理信号三维逆问题研究， Y2090398，浙江省自然科学基金，2010.01-2011.12，8万元，主持。

[10]  磁共振系统磁体设计开发，横向项目，杭州迈新科技有限公司，5万元，2016.05-2017.05，主持。

[11]  基于支持向量回归的全极化综合孔径微波辐射计反演成像方法研究，LY18D060009，浙江省自然科学基金一般项目，8万元，201801-202012，参与（2/6）.

[12]  跨境邮寄物中风险源多维特征挖掘与智能识别技术研究，2018YFC0809201，科技部国家重点研发计划，149万元，201807-202106，参与（11/25）.

(3)已授权发明专利

[1] 蒋明峰，孙慧媛，杨晓城，边境。“基于二维码匹配与图像识别的指针式仪表识别方法”，专利号：ZL201810676486.9，2021.

[2]杨晓城，孙慧媛，边境，蒋明峰，吴龙等。“一种基于巡检机器人的液位仪表读数识别方法”，专利号：ZL201810444697.X， 2021.

[3] 蒋明峰，陆亮，沈益，吴龙。“基于张量积复小波框架的磁共振图像快速重构方法”，专利号：ZL201811124319.X，2020.

[4] 蒋明峰,汪亚明,黄文清,冯杰, 郑俊褒。“一种基于张量分解稀疏约束的三维心脏磁共振成像方法”，专利号：ZL 201410222133.3，2016。

[5] 蒋明峰，汪亚明，黄文清，黄海，蔡霞，曹丽。“基于支持向量回归的心脏电功能成像检测方法”，专利号：ZL 200910152790.4，2010。

(4)学术奖励

[1] 蒋明峰. Application of kernel principal component analysis and support vector regression for reconstruction of cardiac transmembrane potential. “十一五”浙江省自然科学基金优秀论文. 2012.

[2] 蒋明峰，夏灵，汪亚明，寿国法，黄文清。“心脏电生理信号反演问题的求解方法研究”，浙江省高校优秀科研成果二等奖，2010.

[3] 蒋明峰，织物智能提花工艺技术的创新与产业化应用，中国纺织工业联合会科学技术奖二等奖，2015.10， 参与（10/10）.

[4] 浙江省“新世纪151人才工程”第三层次，2011.

[5] 浙江省高校中青年学科带头人, 2013.

[6] 浙江省高校领军人才培养计划“创新领军人才”，2022.