(1)获奖情况 1、在云南省医学会第十九次放射学学术大会“人工智能在现代医学影像成像和后处理中的应用高级研修班”做题为:“基于深度学习的加速磁共振成像重建及分析”的专题讲座。 2、指导的研究生获得“国家奖学金”和“省政府奖学金”各1项。 3、指导的研究生分别在天津大学、西安电子科技大学、深圳大学攻读博士学位。 (2)教学/科研项目 1、昆明理工大学科学计算与系统建模仿真MWORKS平台教学改革研究项目(验证课程:数字信号处理,校级C2),2024-11-09~2025-12-31,在研,主持。 2、云南省基础研究计划项目,202301AT070452,基于自适应稀疏表示和非局部低秩矩阵的欠采样并行三维磁共振成像的重构方法研究,2023/06-2026/05,10万、在研,主持。 3、国家自然科学基金面上项目,62276120,不受昼夜成像条件和模态限制的域自适应行人重识别,2023/01-2026/12,53万、在研,参与。 4、国家自然科学基金地区科学基金项目,61861023,基于并行成像技术的在线动态磁共振成像的实时重构算法研究,2019/01-2022/12,36万、结题,主持。 5、昆明理工大学引进人才科研启动基金项目(云南省省级人培项目),KKSY201703017,并行磁共振成像重构技术研究,2017/11 -2020/10,5万、结题,主持。 (3)论文 [1]Huang Zhenyu,Duan Jizhong*(共一), Xie Yunshuang, Liu Yu. MAFDE-Net: Multipath Attention-Fusion-based Dual-Encoder Network for Undersampled MRI Segmentation[J]. IEEE Transactions on Computational Imaging. 2025,11: 1-16. DOI: 10.1109/TCI.2025.3592319(2025JIF=4.8,中科院二区)在线发表时间:2025-07-24 [2]Ding Peng,Duan Jizhong*(共一), Tao Haibo, Liu Yu. Enhanced Feature Contrastive Self-Supervised Learning Method Based on Deep Unfolding POCS for Accelerated Parallel MRI Reconstruction[J]. IEEE Transactions on Instrumentation and Measurement. 2025, 74: 2527315.Doi:10.1109/TIM.2025.3565051(2025JIF=5.9,中科院二区)发表时间:2025-04-28 [3]Duan Jizhong*, Liu Yu, Wang Junfeng. Accelerated SPIRiT Parallel MR Image Reconstruction based on Joint Sparsity and Sparsifying Transform Learning[J]. IEEE Transactions on Computational Imaging. 2023, 9: 276-288.Doi: 10.1109/TCI.2023.3252260(2023JIF=5.4,中科院二区)发表时间:2023-03-15 [4]Huang Zhenyu,Duan Jizhong*(共一), Xie Yunshuang, Liu Yu.UDNet: Unified Deep Network based on Transformer and Multi-stage Fusion for brain tumor classification from undersampled MRI[J]. Neurocomputing. 2025, 619: 129109. Doi:https://doi.org/10.1016/j.neucom.2024.129109(2025JIF=6.5,中科院二区Top)发表时间:2025-2-28 [5]Duan Jizhong*, Huang Zhenyu(共一), Xie Yunshuang, Wang Junfeng, Liu Yu. Transformer- and joint learning-based dual-domain networks for undersampled MRI segmentation[J]. Medical Physics. 2024, 51(11): 8108-8123.Doi: https://doi.org/10.1002/mp.17358 (2024JIF=3.2,中科院二区)发表时间:2024-11-1 [6]Ding Peng,Duan Jizhong*(共一),Xue Lei,LiuYu, FCSSL: fusion enhanced contrastive self-supervised learning method for parallel MRI reconstruction[J]. Physics in Medicine & Biology. 2024, 69(20): 205018. Doi: https://doi.org/10.1088/1361-6560/ad6d28(2024JIF=3.3,中科院三区)发表时间:2024-10-14 [7]ChenShengyi,Duan Jizhong*(共一),Xinmin Ren, Junfeng Wang, Yu Liu, DFUSNN: zero-shot dual-domain fusion unsupervised neural network for parallel MRI reconstruction[J]. Physics in Medicine & Biology. 2024, 69(10): 105028. Doi:https://doi.org/10.1088/1361-6560/ad3dbc(2024JIF=3.3,中科院三区)发表时间:2024-05-10 [8]Duan Jizhong*, Ren Xinmin. Improved Complex Convolutional Neural Network Based on SPIRiT and Dense Connection for Parallel MRI Reconstruction[J]. IET Signal Processing. 2024, 2024: 7006156. Doi: https://doi.org/10.1049/2024/7006156.(2023JIF=1.7,中科院四区)发表时间:2024-03-14 [9]Duan Jizhong*, Pan Ting, Liu Yu,Wang Junfeng. Non-local low-rank constraint-based self-consistent PMRI reconstruction using eigenvector maps[J]. IETSignalProcessing.2023, 17(3): e12180. doi: 10.1049/sil2.12180.(2023JIF=1.7,中科院四区)发表时间:2023-03-01 [10]Pan Ting,Duan Jizhong*, Wang Junfeng, Liu Yu. Iterative self-consistent parallel magnetic resonance imaging reconstruction based on nonlocal low-rank regularization[J]. Magnetic Resonance Imaging. 2022, 88: 62-75.Doi: https://doi.org/10.1016/j.mri.2022.01.012(2022JIF=3.13,中科院四区)发表时间:2022-05-01 [11]Duan Jizhong*, Liu Chang, Liu Yu, Shang Zhenhong. Adaptive Transform Learning and Joint Sparsity Based PLORAKS Parallel Magnetic Resonance Image Reconstruction[J]. IEEE Access. 2020, 8: 212315-212326. Doi: 10.1109/ACCESS.2020.3039527(2020JIF=3.367,中科院三区)发表时间:2020-11-20 [12]Duan Jizhong, Bao Zhongwen, Liu Yu*. Eigenvector-based SPIRiT Parallel MR Imaging Reconstruction based on Lp pseudo-norm Joint Total Variation, Magnetic Resonance Imaging, 2019, 58: 108-115. Doi: https://doi.org/10.1016/j.mri.2019.01.014(2019JIF=2.053,中科院四区)发表时间:2019-05-01 [13]Duan Jizhong, Liu Yu*, Jing Peiguang. Efficient operator splitting algorithm for joint sparsity-regularized SPIRiT-based parallel MR imaging reconstruction[J]. Magnetic Resonance Imaging. 2018, 46: 81-89. Doi:https://doi.org/10.1016/j.mri.2017.10.013(2018JIF=2.112,中科院四区)发表时间:2018-02-01 [14]Duan Jizhong, Liu Yu*, Zhang Liyi. Bregman Iteration Based Efficient Algorithm for MR Image Reconstruction From Undersampled K-Space Data[J], IEEE Signal Processing Letters, 2013, 20(8): 831-834. Doi: 10.1109/LSP.2013.2268206(2013JIF=1.639,中科院三区)发表时间:2013-08-01 [15]Duan Jizhong*, Su Yan. Improved Sensitivity Encoding Parallel Magnetic Resonance Imaging Reconstruction Algorithm Based on Efficient Sum of Outer Products Dictionary Learning[J]. Journal of Shanghai Jiaotong University (Science). 2025, 30(3): 561-571. Doi: https://doi.org/10.1007/s12204-023-2677-9发表时间:2025-06-01 [16]Duan Jizhong*, Xu Yuhan, Huang Huan. Fast Parallel Magnetic Resonance Imaging Reconstruction Based on Sparsifying Transform Learning and Structured Low-Rank Model[J]. Journal of Shanghai Jiaotong University (Science). 2025, 30(3): 499-509. Doi: https://doi.org/10.1007/s12204-023-2647-2发表时间:2025-06-01 [17]段继忠,刘欢.基于变换学习的快速多切片MRI重建算法[J].北京航空航天大学学报. 2025, 51(7): 2290-2303.Doi:10.13700/j.bh.1001-5965.2023.0561发表时间:2025-07-01 [18]段继忠*,肖琛.基于复数卷积和注意力机制的并行磁共振成像重建[J].北京航空航天大学学报. 2025, 51(1): 85-93.Doi: 10.13700/j.bh.1001-5965.2022.1005发表时间:2025-01-01 [19]李玺兰,段继忠*.基于稀疏变换学习的改进灵敏度编码重建算法[J].北京邮电大学学报. 2022, 45(5): 97-102.Doi: 10.13190/j.jbupt.2021-244发表时间:2022-10-01 [20]段继忠*,钱青青.基于SIDWT和迭代自一致性的快速并行成像重建方法[J].上海交通大学学报. 2023, 57(5): 582-592.Doi: 10.16183/j.cnki.jsjtu.2022.236发表时间:2023-05-01 [21]段继忠*,王成菊.基于多分类字典学习的灵敏度编码重建算法[J].北京航空航天大学学报. 2024, 50(7): 2123-2132.Doi:10.13700/j.bh.1001-5965.2022.0571发表时间:2024-07-01 [22]段继忠,张立毅*,刘昱,孙云山.基于自一致性的磁共振并行成像高效重构算法,天津大学学报, 2014, 47(5): 414-419. (4)知识产权 [1]段继忠,王成菊,一种基于分类图像块字典学习的灵敏度编码重建方法,授权时间:2025-8-12,申请时间:2022-9-9,中国,ZL202211105260.6(已授权) [2]段继忠,钱青青,一种基于SIDWT和迭代自一致性的快速并行成像重建方法,授权时间:2025-8-12,申请时间:2022-9-8,中国,ZL202211098229.4(已授权) [3]段继忠,李玺兰,一种基于稀疏变换学习的改进ESPIRiT重建方法,授权时间:2025-5-23,申请时间:2022-5-7,中国,ZL 202210492674.2(已授权) [4]段继忠,苏艳,一种基于外积有效和字典学习的改进灵敏度编码重建方法,授权时间:2024-10-15,申请时间:2022-6-7,中国,ZL 202210632632.4(已授权) [5]段继忠,李玺兰,一种基于稀疏变换学习的改进灵敏度编码重建方法,授权时间:2024-3-15,申请时间:2021-11-3,中国,ZL 202111296938.9(已授权) [6]段继忠,潘婷,一种基于非局部低秩约束的改进灵敏度编码重构方法,授权时间:2023-10-27,申请时间:2021-10-9,中国,ZL 202111174817.7(已授权) [7]段继忠,潘婷,基于特征向量的自一致性和非局部低秩的并行MRI重构方法,授权时间:2023-9-8,申请时间:2021-8-10,中国,ZL 202110916316.5(已授权) [8]段继忠,和晓珣,一种基于Lp范数联合全变分的并行磁共振成像重构方法,授权时间:2022-10-28,申请时间:2020-12-31,中国,ZL 202011644181.3(已授权) [9]段继忠,潘婷,一种非局部低秩约束的自校准并行磁共振成像重构方法,授权时间:2022-3-1,申请时间:2021-4-26,中国,ZL 202110452944.2(已授权) [10]段继忠,郝玲,一种基于难样本混淆增强特征鲁棒性的行人重识别方法,授权时间:2022-3-22,申请时间:2021-01-13,中国,ZL 202110028392.2(已授权) [11]段继忠,刘畅,基于变换学习的局部空间邻域并行磁共振成像重构方法,授权时间:2022-2-25,申请时间:2020-6-27,中国,ZL 202010593729.X(已授权) [12]段继忠,鲍中文,一种基于变换学习和联合稀疏性的迭代自一致性并行成像重构方法,授权时间:2022-5-24,申请时间:2019-1-22,中国,ZL201910056437.X(已授权) [13]段继忠,鲍中文,基于特征向量的自一致性的联合全变分Lp伪范数的并行磁共振成像重构方法,授权时间:2022-6-21,申请时间:2019-1-16,中国,ZL201910046669.7(已授权) [14]段继忠,贾伟,一种基于级联并行卷积网络的磁共振图像重建方法,授权时间:2022-8-2,申请时间:2020-8-9,中国,ZL202010792387.4(已授权) [15]段继忠,罗仁泽,苏赋,邓魁,郑勉,汪敏,曹玉英,基于自一致性的含联合全变分的并行磁共振成像高质量重构方法,授权时间:2017-12-5,申请时间:2015-10-16,中国, ZL 201510676797.1(已授权) [16]段继忠,罗仁泽,苏赋,邓魁,郑勉,曹玉英,汪敏,一种基于自一致性的并行磁共振成像快速重构方法,授权时间:2019-7-16,申请时间:2016-5-18,中国,ZL 201610331573.1(已授权) |