Homepage of Chengyan Wang(王成彦个人主页，复旦大学青年副研究员、硕导)


	王成彦的个人主页 (中文,English)
	青年副研究员、硕导

	复旦大学人类表型组研究院

	Email: wangcy@fudan.edu.cn

	联系方式: (86) 151-0111-7286

	研究小组：计算感知实验室

个人简历

工作经历

专著

个人简历

王成彦，复旦大学，人类表型组研究院，青年副研究员，从事磁共振影像重建、放射组学、深度学习和表型组学等方面的研究。目前主要的研究方向是：1）基于深度学习的多模态影像分析和重建；2）心脏高分辨率组织定量成像和功能影像表型提取；3）高分辨弥散张量成像及其临床应用。目前以第一作者或通讯作者(含共同)在Radiology、MedIA、Neuroimage、IEEE JBHI、MRM等期刊发表论文30余篇，在CVPR、NeurIPS、MICCAI、ISMRM、RSNA等国际会议上发表会议论文/摘要70余篇，副主编（译）论著1部（“医学影像与人工智能：基于、应用和风险”），申请国家发明专利10项，授权2项。目前作为课题负责人承担国家自然科学基金、国自然国际(地区)交流项目和上海市青年科技英才扬帆计划各1项，参与国家及省部级项目3项。

工作经历

2019/07 – 至今，复旦大学人类表型组研究院，青年副研究员

2018/04 - 2019/04，伊利诺伊大学厄巴纳-香槟分校，访问博士后

2017/06 - 2019/06，上海交通大学生物医学工程学院，博士后

2016/09 - 2017/06，美国哈佛医学院心血管影像中心，访问学者

2012/09 - 2017/07，北京大学生物力学与医学工程专业，博士

研究方向

磁共振影像重建、放射组学、心血管成像、深度学习和表型组学等。

招生专业

生物信息学

生物医学工程

医学影像学

人工智能

课题项目

英国皇家学会-国家自然科学基金国际(地区)合作交流项目(NSFC-RS(中英))，IEC\NSFC\211235，基于注意力机制的生成对抗网络的快速全心脏4D电影成像，2022/03-2024/03，联合主持

国家自然科学基金青年项目，62001120，运动补偿的三维心肌组织定量成像技术研究及其在心肌梗死后水肿评估中的应用，2021/01-2023/12，主持

上海市青年科技英才扬帆计划，20YF1402400，基于运动补偿的心肌纤维束跟踪成像研究，2020/07-2023/06，主持

国家自然科学基金面上项目，81871083，基于全脑高分辨率磁共振波谱成像技术的强迫症患者神经代谢异常研究，2019/01-2022/12，参与

国家自然科学基金面上项目，81571666，基于柔性线圈的下肢和足部磁共振无创灌注成像研究，2016/01-2019/12，参与

获奖情况

2019 ISMRM Magna Cum Laude Merit Award：Simultaneous Reconstruction of Multiple b-Values DWI using a Joint Convolutional Neural Network

2017 ISMRM Magna Cum Laude Merit Award：Comparison of BOLD-contrast imaging and DW imaging for early prediction of renal damage after microemboli-induced acute kidney injury in animal model

2017 ISMRM Magna Cum Laude Merit Award：A feasibility study of using noninvasive renal oxygenation imaging to delineate different severities of renal ischemia in atheroembolic renal disease model

研究成果

[1]Lyu J, Li G, Wang C*, Qin C, Wang S, Qin J. Region-focused multi-view transformer-based generative adversarial network for cardiac cine MRI reconstruction. Medical Image Analysis, 2023: 102760. https://doi.org/10.1016/j.media.2023.102760

[2]Lyu J, Sui B, Wang C*, et al. Adaptive Feature Aggregation based Multi-task Learning for Uncertainty-guided Semi-supervised Medical Image Segmentation. Expert Systems with Applications, 2023.

[3]Wang C, Shi Z, Li Y, et al. Protocol for Brain Magnetic Resonance Imaging and Extraction of Imaging-Derived Phenotypes from the China Phenobank Project. Phenomics, 2023: 1-15.

[4]Wang C#, Huang Y#, Liu C, Liu F, Hu X, Kuang X, An W, Liu C, Liu Y, Liu S, He R, Wang H, Qi X*. Diagnosis of Clinically Significant Portal Hypertension using CT/MRI-based Vascular Model. Radiology 2023. https://doi.org/10.1148/radiol.221648

[5]Lv J, Li G, Chen W, Wang C*, Li R*. Multi-Channel Generative Adversarial Network–Based Calibration-free Liver Diffusion-Weighted Imaging with Joint Coil Sensitivity Estimation and Reconstruction. Frontiers in Oncology. 2023.

[6]Wang S#, Qin C#, Wang C#, Wang K, Wang H, Chen C, Ouyang C, Kuang X, Dai C, Mo Y, Shi Z, Dai C, Chen X, Wang H, Bai W. The Extreme Cardiac MRI Analysis Challenge under Respiratory Motion (CMRxMotion). arXiv:2210.06385, 2022.

[7]Wang F, Zhang H, Dai F, Chen W, Xu S, Yang Z, Shen D, Wang C*, Wang H*. Multiple B-Value Model-Based Residual Network (MORN) for Accelerated High-Resolution Diffusion-Weighted Imaging. IEEE Journal of Biomedical and Health Informatics 2022, 26(9): 4575-4586.

[8]Yan S, Wang C, Chen W, Lyu J*. Swin transformer-based GAN for multi-modal medical image translation. Frontiers in Oncology 2022, 12: 942511.

[9]Qian Yu, Yifei Huang, Xiaoguo Li, Michael Pavlides, Dengxiang Liu, Hongwu Luo, Huiguo Ding, Weimin An, Fuquan Liu, Changzeng Zuo, Chunqiang Lu, Tianyu Tang, Yuancheng Wang, Shan Huang, Chuan Liu, Tianlei Zheng, Ning Kang, Changchun Liu, Jitao Wang, Seray Akçalar, Emrecan Çelebioğlu, Evren Üstüner, Sadık Bilgiç, Qu Fang, Chi-Cheng Fu, Ruiping Zhang, Chengyan Wang, Jingwei Wei, Jie Tian, Necati Örmeci, Zeynep Ellik, Özgün Ömer Asiller, Shenghong Ju, Xiaolong Qi*. An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension. Cell Reports Medicine 2022, 3(3): 100563.

[10]Wang C, Huang Y, Liu C, Liu F, Hu X, Kuang X, An W, Liu C, Liu Y, Liu S, He R, Wang H, Qi X*. Development and Validation of a Hepatic Vascular Geometrical Model for Noninvasive Diagnosis of Clinically Significant Portal Hypertension in Cirrhosis. SSRN Electronic Journal 2022.

[11]Chen Y, Li R, Yang Y, Ma D, Zhou J, Wang C, Kong L, Chen Y, Yan F, Feng Y*. Correlation analysis of structural and biomechanical properties of hepatocellular carcinoma tissue. Journal of Biomechanics, 2022, 141: 111227.

[12]Li Y, He N, Zhang C, Liu Y, Li J, Sun B, Lai Y, Li H, Wang C, Haacke EM, Yan F*, Li D*. Mapping Motor Pathways in Parkinson’s Disease Patients with Subthalamic Deep Brain Stimulator: A Diffusion MRI Tractography Study. Neurology and therapy, 2022, 11(2): 659-677.

[13]Zheng R#, Wang Q#, Lv S, Li C, Wang C, Chen W, Wang H*. Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM. IEEE Trans Med Imaging, 2022, 41(10): 2965-2976.

[14]Wang L#, Wang C#, Wang F, Chu Y, Yang Z, Wang H*. EPI phase error correction with deep learning (PEC‐DL) at 7 T. Magnetic Resonance in Medicine, 2022, 88(4): 1775-1784.

[15]Hu X, Zhou J, Li Y, Wang Y, Guo J, Sack I, Chen W, Yan F, Li R*, Wang C*. Added Value of Viscoelasticity for MRI-Based Prediction of Ki-67 Expression of Hepatocellular Carcinoma Using a Deep Learning Combined Radiomics (DLCR) Model. Cancers. 2022, 14(11):2575.

[16]Wang C#, Zheng L#, Li Y, Xia S, Lv J, Hu X, Zhan W, Yan F, Li R, Ren X*. Noninvasive Assessment of Liver Fibrosis and Inflammation in Chronic Hepatitis B: A Dual-task Convolutional Neural Network (DtCNN) Model Based on Ultrasound Shear Wave Elastography. J Clin Transl Hepatol. 2022, 10(6):1077-1085.

[17]Zhang H#, Wang C#, Chen W, Wang F, Yang Z, Xu S, Wang H*. Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI. Neuroimage. 2021, 244: 118632.

[18]Zhang B, Yao Z, Gao W, Wang C, Kong H, Zhang J, Yang M*. Dynamic R2'Imaging can Be a Biomarker for Diagnosing and Staging Early Acute Kidney Injury in Animals. Frontiers in Medicine, 2021, 24;8:775042.

[19]Sui B, Lv J*, Tong X, Li Y, Wang C. Simultaneous Image Reconstruction and Lesion Segmentation in Accelerated MRI Using Multi-Tasking Learning. Medical Physics. 2021, 48(11): 7189-7198.

[20]Wang C*, Li Y, Lv J, Jin J, Hu X, Kuang X, Chen W, Wang H*. Recommendation for Cardiac Magnetic Resonance Imaging-Based Phenotypic Study: Imaging Part. Phenomics. 2021, 1(4): 151-170.

[21]Wang F, Zhang H, Dai F, Chen W, Wang C*, Wang H*. MAGnitude-Image-to-Complex K-space (MAGIC-K) Net: A Data Augmentation Network for Image Reconstruction. Diagnostics, 2021, 11(10): 1935.

[22]Li G, Lv J*, Tong X, Wang C*, Yang G. High-Resolution Pelvic MRI Reconstruction Using a Generative Adversarial Network with Attention and Cyclic Loss. IEEE Access. 2021, 9: 105951-105964.

[23]Wang K, Wang S, Xiong M, Wang C*, Wang H*. Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics. MICCAI 2021. Springer, Cham, 2021: 33-42.

[24]Li G, Wang C*, Lv J. Current status of deep learning in abdominal image reconstruction. Artificial Intelligence in Medical Imaging. 2021, 2(4):9.

[25]Wang C#, Shi Z#, Yang M, Huang L, Fang W, Jiang L, Ding J, Wang H. Deep learning-based identification of acute ischemic core and deficit from non-contrast CT and CTA. J Cereb Blood Flow Metab. 2021, 41(11): 3028-3038.

[26]Lv J, Wang C*, Yang G*. PIC-GAN: A Parallel Imaging Coupled Generative Adversarial Network for Accelerated Multi-Channel MRI Reconstruction. Diagnostics. 2021, 11(1): 61.

[27]Zheng R, Wang L, Wang C, Yu X, Chen W, Li Y, Li W, Yan F, Wang H, Li R. Feasibility of Automatic Detection of Small Hepatocellular Carcinoma (≤2 cm) in Cirrhotic Liver based on Pattern Matching and Deep Learning. Physics in Medicine and Biology. 2021, 66: 085014.

[28]Lv J, Li G, Tong X, Chen W, Huang J, Wang C*, Yang G*. Transfer learning enhanced generative adversarial networks for multi-channel MRI reconstruction. Comput Biol Med. 2021, 134:104504.

[29]Zheng R, Shi C, Wang C, Shi N, Qiu T, Chen W, Shi Y, Wang H. Imaging-Based Staging of Hepatic Fibrosis in Patients with Hepatitis B: A Dynamic Radiomics Model Based on Gd-EOB-DTPA-Enhanced MRI. Biomolecules. 2021, 11(2):307.

[30]Li G, Lv J* and Wang C. A Modified Generative Adversarial Network Using Spatial and Channel-Wise Attention for CS-MRI Reconstruction. IEEE Access. 2021, 9:83185-83198.

[31]Zhao X, Shi J, Dai F, Wei L, Zhang B, Yu X, Wang C, Zhu Z, Wang H. Brain development from newborn to adolescence: Evaluation by neurite orientation dispersion and density imaging. Frontiers in Human Neuroscience. 2021, 15: 122.

[32]Li Y, Sethi SK, Zhang C, Miao Y, Yerramsetty KK, Palutla VK, Gharabaghi S, Wang C, He N, Yan F, Haacke EM. Iron Content in Deep Gray Matter as a Function of Age Using Quantitative Susceptibility Mapping: A Multicenter Study. Frontiers in Neuroscience. 2021, 14: 1389.

[33]Wang C, Liang YC, Wu Y, Yang D，Zhao SW, Du YP. Correction of Out-of-FOV Motion Artifacts using Convolutional Neural Network Derived Prior Image. Magnetic Resonance Imaging. 2020, 71: 93-102.

[34]Kong H, Chen B, Zhang X, Wang C, Yang M, Yang L, Wang X, Zhang J. Quantitative renal function assessment of atheroembolic renal disease using view-shared compressed sensing based dynamic-contrast enhanced MR imaging: An in vivo study. Magnetic Resonance Imaging. 2020, 65:67-74.

[35]Lv J, Tong X, Wang C*. Parallel Imaging With a Combination of SENSE and Generative Adversarial Networks (GAN). Quantitative Imaging in Medicine and Surgery. 2020, 10(12): 2260–2273.

[36]Zhang B#, Wang C#, Wang H, Kong H, Gao F, Wang X, Yang M, and Zhang J. Feasibility of MRI based Oxygenation Imaging for the Assessment of Acute Limb Ischemia. Annals of Translational Medicine. 2020, 8(6): 315.

[37]Wang C#, Zhang B#, Wang H, Kong H, Gao F, Wang X, Yang M, Zhang J. A feasibility study of using noninvasive renal oxygenation imaging for the early assessment of ischemic acute kidney injury in an embolization model. Magnetic Resonance Imaging. 2019, 63: 178-184.

[38]Wang H*, Zheng R, Dai F, Wang Q, Wang C*. High-field MR Diffusion-weighted Image Denoising Using a Joint Denoising Convolutional Neural Network. Journal of Magnetic Resonance Imaging. 2019, 50(6): 1937-1947.

[39]Zhang BH, Wang Y, Wang C, Wang HC, Kong H, Zhang J, Zou Y, Yang M. Comparison of blood oxygen level-dependent imaging and diffusion-weighted imaging in early diagnosis of acute kidney injury in animal models. Journal of Magnetic Resonance Imaging. 2019, 50(3): 719-724.

[40]Wang Y, Zhang R, Zhang B, Wang C, Wang H, Zhang X, Zhao K, Yang M, Wang X, Zhang J. Simultaneous R2, R2' and R2* measurement of skeletal muscle in a rabbit model of unilateral artery embolization. Magnetic Resonance Imaging. 2019, 61:149-157.

[41]Wang C#, Jang J#, Neisius U, Nezafat M, Fahmy A, Kang J, Rodriguez J, Goddu B, Pierce P, Berg S, Zhang J, Wang XY, Nezafat R. Black blood myocardial T2 mapping. Magnetic resonance in medicine. 2019, 81(1): 153-166.

[42]Kong H, Wang C, Gao F, Zhang X, Yang M, Yang L, Wang X, Zhang J. Early assessment of acute kidney injury using targeted field of view diffusion-weighted imaging: An in vivo study. Magnetic Resonance Imaging. 2019, 57: 1-7.

[43]Wang C#, Zhang R#, Zhang X, Wang H, Zhao K, Jin L, Zhang J, Wang X, Fang J. Simultaneous Dynamic R2, R2' and R2* Measurement Using Periodic π Pulse Shifting Multiecho Asymmetric Spin Echo Sequence and Moving Estimation Strategy: A Feasibility Study for Lower Extremity Muscle. Magnetic resonance in medicine. 2017, 77(2): 766-773.

[44]Gao G, Wang C, Zhang X, Hu J, Yang X, Wang H, Zhang J, Wang X. Quantitative Analysis of Diffusion-weighted MR Images: Differentiation Between Prostate Cancer and Normal Tissue Based on Computer-aided Diagnosis System. Science China Life Sciences. 2017, 60(1): 37-43.

[45]Wang C#, Zhang R#, Wang R, Jiang L, Zhang X, Wang H, Zhao K, Jin L, Zhang J, Wang X, Fang J. Noninvasive Measurement of Renal Oxygen Extraction Fraction Under the Influence of Respiratory Challenge. Journal of Magnetic Resonance Imaging. 2016, 44(1): 230-237.

[46]Wang C#, Zhang R#, Zhang X, Wang H, Zhao K, Jin L, Zhang J, Wang X, Fang J. Noninvasive Measurement of Lower Extremity Muscle Oxygen Extraction Fraction under Cuff Compression Paradigm. Journal of Magnetic Resonance Imaging. 2016, 43(5): 1148-1158.

[47]Wang C#, Zhao K#, Zhang R, Jiang L, Wang R, Zhang X, Wang H, Jin L, Zhang J, Wang X, Fang J. Evaluation of Renal Oxygenation Change Under the Influence of Carbogen Breathing Using a Dynamic R2, R2' and R2* Quantification Approach. NMR in Biomedicine. 2016, 29(11): 1601-1607.

[48]Zhao K, Wang C, Hu J, Yang X, Wang H, Li FY, Zhang X, Zhang J, Wang X. Prostate Cancer Identification: Quantitative Analysis of T2-weighted MR Images Based on a Back Propagation Artificial Neural Network Model. Science China Life Sciences. 2015, 58(7): 666-673.

专著

胡娟, 杨斌, 王成彦（副主编）, 何波。医学影像与人工智能-机遇、应用和风险（译）。人民卫生出版社, 2022

会议论文（部分）

[1]Zhang H, Wang C, Wu P, Chen W, Wang H. High-Resolution Diffusion Weighted Imaging of Hepatocellular Carcinoma (HCC). ISMRM, London, England, UK 2022 (Oral #2713)

[2]Lyu J, Sui B, Wang C*, Tian Y, Dou Q, Qin J. DuDoCAF: Dual-Domain Cross-Attention Fusion with Recurrent Transformer for Fast Multi-contrast MR Imaging[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2022: 474-484.

[3]Li G, Lyu J*, Wang C, Dou Q, Qin J. WavTrans: Synergizing Wavelet and Cross-Attention Transformer for Multi-contrast MRI Super-Resolution[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2022: 463-473.

[4]Li G, Lv J, Tian Y, Dou Q, Wang C, Xu C, Qin J. Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022: 20636-20645.

[5]C Wang, Y Huang, C Liu, F Liu, X Hu, X Kuang, W An, C Liu, Y Liu and X Qi. Development and validation of a vascular geometrical model for noninvasive diagnosis of CSPH in cirrhosis (CHESS1802). EASL International Liver Congress, London, England 2022 (Poster # FRI-224). DOI: 10.3252/pso.eu.ILC2022.2022.

[6]Wang CY, Liang YC, Wu Y, Yang D, Du YP. Simultaneous Reconstruction of Multiple b-Values DWI using a Joint Convolutional Neural Network. ISMRM, Montreal, Canada 2019 (Oral # 0231) (Magna Cum Laude Merit Award)

[7]Wang CY, Jang J, Fahmy A, Kang J, Goddu B, Berg S, Zhang J, Wang XY, Manning W, Nezafat R. Myocardial T2 mapping using a Black-blood hEart-rate Adaptive T2-prepared bSSFP (BEATS) sequence. ISMRM, Paris, France 2018 (Oral #1456)

[8]Wang CY, Kong HJ, Gao F, Huang WJ, Ding L, Wang R, Jiang L, Jia Y, Xu H, Wang H, Zhang XD, Yang L, Zhang J, Wang XY, Fang J. Comparison of BOLD-contrast imaging and DW imaging for early prediction of renal damage after microemboli-induced acute kidney injury in animal model. ISMRM, Hawaii, USA 2017 (Oral #0825) (Magna Cum Laude Merit Award)

[9]Wang CY, Zhang R, Jiang L, Wang R, Zhang XD, Wang H, Zhao K, Jin LX, Zhang J, Wang XY, Fang J. Noninvasive Measurement of Single Renal Oxygen Extraction Fraction using Focused Asymmetric Spin Echo Approach - a feasibility study. ISMRM, Singapore 2016 (Oral #0268)

[10]Wang CY, Zhang R, Zhang XD, Wang H, Zhao K, Zhang J, Wang XY, Fang J. Skeletal Muscle Oxygen Extraction Fraction Measurement - At Rest and During Ischemia. ISMRM, Toronto, Canada 2015 (Oral #0749)

专利

[1]王鹤，王繁文，王成彦。一种基于单次激发的弥散加权成像扫描重建方法与系统。专利号：202111216100.4（实审中）

[2]王成彦，王可欣，王鹤，肝静脉压力梯度的测量方法、测量系统、电子设备及介质，专利号：2021107732655(2021)

[3]庄吓海，高尚奇，靳建华，周杭琪，王成彦，一种无监督的心脏磁共振参数定量图像重建方法，专利号：202110687905.0(2021)

[4]刘慧慧，肖国栋，曹勇军，刘春风，王成彦，方文星，杨鸣，一种基于能谱增强CT的图像处理方法，专利号：202010295220.7(2020)

[5]杨鸣，王成彦，蒋李，方文星，基于脑血管CT影像的图像处理方法及图像处理装置，专利号：202010089706.5(2020)

[6]于航，王成彦，王鹤，一种基于深度学习的多模态肝脏磁共振影像配准系统，专利号：202010845127.9(2020)

[7]王成彦，蒋李，一种针对肿瘤影像数据的智能读片系统，专利号：ZL201810380971.1(2018)

[8]王成彦，蒋李，一种用于多参数磁共振影像的前列腺自动分区技术，专利号：2018103793253(2018)

[9]王成彦，杜一平，一种心脏血池抑制弛豫参数成像方法，专利号： 2018105697922(2018)，已授权

[10]王成彦，张锐，王鹤，金立新，王霄英，张珏，方竞，一种基于磁共振成像的无创动态测量肌肉氧摄取率的方法，专利号： 2015105770958(2015)

[11]王成彦，张锐，王鹤，金立新，王霄英，张珏，方竞，一种无创动态测量组织R2，R2*和R2'参数图像的磁共振成像方法，专利号：2015105769931(2015)

[12]王成彦，王鹤，胡娟，陈双娟，张珏，王霄英，方竞，基于多参数磁共振影像的前列腺癌计算机辅助识别系统，专利号：2013103705315(2013)

王成彦的个人主页 (中文,English)