研究员
朱燕杰
| 职 称： 研究员 |
| 学 历： 博士 |
| 邮 箱： yj.zhu@siat.ac.cn |
| 研究领域：心脏快速磁共振成像和智能分析 |
朱燕杰，研究员，博士生导师，深圳市高层次人才（B类），主要从事医学磁共振成像相关的研究。作为项目负责人承担国家重点研发计划课题,国家自然科学基金面上（2项）和青年项目。近年来，在Magnetic
Resonance in Medicine, IEEE trans Medical Imaging, Medical Physics,
Physics in Medicine and Biology等领域内权威期刊发表论文40余篇,主译快速成像专著一部；授权发明专利30余项，快速磁共振成像专利获得中国专利优秀奖，获广东省技术发明一等奖、四川省科技进步一等奖等多项奖励。作为骨干参与研发国产首型3T超导磁共振系统，实现了实时心脏电影成像，驰豫定量成像等技术的转化，在百余家医院应用推广。
1. 国家重点研发计划课题，磁共振快速成像及国产设备产业应用，
2020.12--2025.11，课题负责人
2.国家自然科学基金面上项目，心脏重构中微观结构变化的在体心肌磁共振弥散定量成像研究
2020.01-2023.12 项目负责人。
3. 国家自然科学基金面上项目，磁共振T1T2联合对比成像精准检测心肌水肿的关键问题研究
2018.01-2021.12 项目负责人
4. 中国科学院磁共振联盟项目，T1rho定量成像序列开发及国产设备实现
2020.9-2022.8 项目负责人
5. 深圳市优秀科技创新人才培养项目，基于学习模型的超高场代谢定量磁共振成像研究
2022.4-2025.4 项目负责人
2020.12--2025.11，课题负责人
2.国家自然科学基金面上项目，心脏重构中微观结构变化的在体心肌磁共振弥散定量成像研究
2020.01-2023.12 项目负责人。
3. 国家自然科学基金面上项目，磁共振T1T2联合对比成像精准检测心肌水肿的关键问题研究
2018.01-2021.12 项目负责人
4. 中国科学院磁共振联盟项目，T1rho定量成像序列开发及国产设备实现
2020.9-2022.8 项目负责人
5. 深圳市优秀科技创新人才培养项目，基于学习模型的超高场代谢定量磁共振成像研究
2022.4-2025.4 项目负责人
1.Y Zhu, Y Liu, L Ying, Z Qiu, Q Liu, S Jia, H Wang, X Peng, X Liu, H Zheng, D Liang, A 4-
minute solution for submillimeter whole-brain T1ρ quantification, Magn Reson Med, 2021,
85(6):3299-3307.
2. Y Liu, L Ying, W Chen, Z Cui, Q Zhu, X Liu, H Zheng, D Liang, Y Zhu*, Accelerating the
3D T1ρ mapping of cartilage using a signal-compensated robust tensor principal component
analysis model, Quant Imaging Med Surg 2021;11(8):3376-3391
3. F Yang, L Wang, J Wang, L Pu, Y Xu, W Li, K Wan, D Yang, J Sun, Y Han, Y Zhu*, Y Chen*,
Prognostic value of fast semi-automated left atrial long-axis strain analysis in hypertrophic
cardiomyopathy, J Cardiovasc Magn Reson, 2021, 23:36.
4. J Cheng, Z Cui, W Huang, Z Ke, L Ying, H Wang, Y Zhu, D Liang, Learning data consistency
and its application to dynamic MR imaging, IEEE Trans Med Imaging, 2021, 40, 3140 – 3153.
5. J Wang, Y Li, F Yang, L Bravo, K Wan, Y Xu, W Cheng, J Sun, Y Zhu, T Zhu, G. Gkoutos,
Y Han, Y Chen, Fractal Analysis: Prognostic Value of Left Ventricular Trabecular Complexity
Cardiovascular MRI in Participants with Hypertrophic Cardiomyopathy, Radiology 2021;
298:71–79.
6. W Huang, Z Ke, Z Cui, J Cheng, Z Qiu, S Jia, L Ying, Y Zhu, D Liang, Deep low-Rank plus
sparse network for dynamic MR imaging, Medical Image Analysis, 2021, 73 102190.
7. Z Ke, C Jing, L Ying, H Zheng, Y Zhu*, D Liang, An unsupervised deep learning method for
multi-coil cine MRI, Phys Med Biol, 2020,65:235041.
8. J Wang, F Yang, W Liu, J Sun, Y Han, D Li, G Gkoutos, Y Zhu*, Y Cheng*, Radiomic Analysis
of Native T1 Mapping Images Discriminates Between MYH7 and MYBPC3-Related
Hypertrophic Cardiomyopathy, J Magn Reson Imaging, 2020;52:1714–1721.
9. Y Zhu, Y Liu, L Ying, X Liu, H Zheng, D Liang, Bio-SCOPE: Fast biexponential T1ρ
mapping of the brain using signal-compensated low-rank plus sparse matrix decomposition,
Magn Reson Med, 2020, 83:2092-2106.
10. M Zhang, M Li, J Zhou, Y Zhu, S Wang, D Liang, Y Chen, Q Liu, High-dimensional
embedding network derived prior for compressive sensing MRI reconstruction, Medical Image
Analysis, 2020, 64, 101717
11. Y Zhu, F Ahmed, C Duan, S Nakamori, R Nezafat, Automated Myocardial T2 and
Extracellular Volume Quantification in Cardiac Magnetic Resonance Using Transfer Learning
Based Myocardium Segmentation, Radiology: Artificial Intelligence, 2020, 291:e190034.
12. Y Zhu, J Kang, C Duan, M Nezafat, U Neisius, J Jang, R Nezafat, Integrated Motion
Correction and Dictionary Learning for Free-breathing Myocardial T1 Mapping, Magn Reson
Med, 2019, 73: 263-272
13. C Duan, Y Zhu,J Jang, J Rodriguez, U Neisius, A Fahmy, R Nezafat, Non-contrast myocardial
infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence
at 1.5T, Magn Reson Med. 2019;81:3192–3201.
14. Y Zhu，D Yang, L Zou, Y Chen, X Liu, Y Chung, T2STIR Preparation for Single-shot
Myocardial Edema Imaging, J Cardiovasc Magn Reson 2019, 21:72.
15. Y Zhu, Y Liu, L Ying, X Peng, Y Wang, J Yuan, X Liu, D Liang, SCOPE: signal compensation
for low-rank plus sparse matrix decomposition for fast parameter mapping, 2018, Phys Med
Biol 63, 185009
16. Y Zhu , X Peng, Y Wu, et.al, Direct Diffusion Tensor Estimation Using Model-Based Method
with Spatial and Parametric Constraints, Med Phys 2017, 44(2).
minute solution for submillimeter whole-brain T1ρ quantification, Magn Reson Med, 2021,
85(6):3299-3307.
2. Y Liu, L Ying, W Chen, Z Cui, Q Zhu, X Liu, H Zheng, D Liang, Y Zhu*, Accelerating the
3D T1ρ mapping of cartilage using a signal-compensated robust tensor principal component
analysis model, Quant Imaging Med Surg 2021;11(8):3376-3391
3. F Yang, L Wang, J Wang, L Pu, Y Xu, W Li, K Wan, D Yang, J Sun, Y Han, Y Zhu*, Y Chen*,
Prognostic value of fast semi-automated left atrial long-axis strain analysis in hypertrophic
cardiomyopathy, J Cardiovasc Magn Reson, 2021, 23:36.
4. J Cheng, Z Cui, W Huang, Z Ke, L Ying, H Wang, Y Zhu, D Liang, Learning data consistency
and its application to dynamic MR imaging, IEEE Trans Med Imaging, 2021, 40, 3140 – 3153.
5. J Wang, Y Li, F Yang, L Bravo, K Wan, Y Xu, W Cheng, J Sun, Y Zhu, T Zhu, G. Gkoutos,
Y Han, Y Chen, Fractal Analysis: Prognostic Value of Left Ventricular Trabecular Complexity
Cardiovascular MRI in Participants with Hypertrophic Cardiomyopathy, Radiology 2021;
298:71–79.
6. W Huang, Z Ke, Z Cui, J Cheng, Z Qiu, S Jia, L Ying, Y Zhu, D Liang, Deep low-Rank plus
sparse network for dynamic MR imaging, Medical Image Analysis, 2021, 73 102190.
7. Z Ke, C Jing, L Ying, H Zheng, Y Zhu*, D Liang, An unsupervised deep learning method for
multi-coil cine MRI, Phys Med Biol, 2020,65:235041.
8. J Wang, F Yang, W Liu, J Sun, Y Han, D Li, G Gkoutos, Y Zhu*, Y Cheng*, Radiomic Analysis
of Native T1 Mapping Images Discriminates Between MYH7 and MYBPC3-Related
Hypertrophic Cardiomyopathy, J Magn Reson Imaging, 2020;52:1714–1721.
9. Y Zhu, Y Liu, L Ying, X Liu, H Zheng, D Liang, Bio-SCOPE: Fast biexponential T1ρ
mapping of the brain using signal-compensated low-rank plus sparse matrix decomposition,
Magn Reson Med, 2020, 83:2092-2106.
10. M Zhang, M Li, J Zhou, Y Zhu, S Wang, D Liang, Y Chen, Q Liu, High-dimensional
embedding network derived prior for compressive sensing MRI reconstruction, Medical Image
Analysis, 2020, 64, 101717
11. Y Zhu, F Ahmed, C Duan, S Nakamori, R Nezafat, Automated Myocardial T2 and
Extracellular Volume Quantification in Cardiac Magnetic Resonance Using Transfer Learning
Based Myocardium Segmentation, Radiology: Artificial Intelligence, 2020, 291:e190034.
12. Y Zhu, J Kang, C Duan, M Nezafat, U Neisius, J Jang, R Nezafat, Integrated Motion
Correction and Dictionary Learning for Free-breathing Myocardial T1 Mapping, Magn Reson
Med, 2019, 73: 263-272
13. C Duan, Y Zhu,J Jang, J Rodriguez, U Neisius, A Fahmy, R Nezafat, Non-contrast myocardial
infarct scar assessment using a hybrid native T1 and magnetization transfer imaging sequence
at 1.5T, Magn Reson Med. 2019;81:3192–3201.
14. Y Zhu，D Yang, L Zou, Y Chen, X Liu, Y Chung, T2STIR Preparation for Single-shot
Myocardial Edema Imaging, J Cardiovasc Magn Reson 2019, 21:72.
15. Y Zhu, Y Liu, L Ying, X Peng, Y Wang, J Yuan, X Liu, D Liang, SCOPE: signal compensation
for low-rank plus sparse matrix decomposition for fast parameter mapping, 2018, Phys Med
Biol 63, 185009
16. Y Zhu , X Peng, Y Wu, et.al, Direct Diffusion Tensor Estimation Using Model-Based Method
with Spatial and Parametric Constraints, Med Phys 2017, 44(2).