Dr. Jianwen Luo received his B.S. (2000) and Ph.D. (2005) degrees (with honors) in Biomedical Engineering from Tsinghua University, Beijing, China. From 2005 to 2009, he was a Postdoctoral Research Scientist, and from 2009 to 2011, he served as an Associate Research Scientist in the Department of Biomedical Engineering at Columbia University, New York, NY, USA. In 2011, he joined the Department of Biomedical Engineering, School of Medicine, Tsinghua University, as a Tenure-Track Associate Professor. He was promoted to Tenured Associate Professor in 2017 and became a Full Professor in 2023. Also in 2023, he was appointed as a Chang Jiang Scholar Distinguished Professor by the Ministry of Education of China. He is currently a Full Professor in the School of Biomedical Engineering at Tsinghua University.
Dr. Luo's primary research focuses on ultrasound imaging, encompassing elasticity imaging, cardiovascular imaging, ultrasensitive Doppler imaging, super-resolution ultrasound localization microscopy, and the application of artificial intelligence in ultrasound imaging and image computation.
Dr. Luo received the Excellent Young Scientists Fund from the National Natural Science Foundation of China (NSFC) in 2013. He was also supported by the National Key R&D Program of China in 2016 and 2020. He has authored or co-authored over 380 publications, including more than 200 peer-reviewed articles in international SCI-indexed journals and 120 conference papers. As of November 1, 2025, his work has been cited over 9,500 times, with an H-index of 50.
Dr. Luo has served as a member of the IEEE Engineering in Medicine and Biology Society (EMBS) Technical Committee on Biomedical Imaging and Image Processing (BIIP) from 2015 to 2025. He has also been a member of the Technical Program Committee for the IEEE International Ultrasonics Symposium (IUS) since 2019. His editorial roles include serving as an Associate Editor for IEEE Transactions on Medical Imaging (2019–2025) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2019–2024). He has been an Editorial Board Member of the Journal of Ultrasound in Medicine since 2009 and joined the Editorial Board of Ultrasonics in 2021.
Focused on research into new methods for medical ultrasound imaging and diagnosis
Professor LUO Jianwen has long been dedicated to research on medical ultrasound imaging methods, with a particular focus on ultrasound elastography and new diagnostic approaches for cardiovascular diseases and liver fibrosis. In recent years, he has further conducted research on ultra-fast ultrasound Doppler blood flow imaging, ultrasound brain function imaging, super-resolution ultrasound imaging, and ultrasound imaging and image analysis based on deep learning.
(1) Ultrasound elastography methods
Novel ultrasound imaging sequences based on technologies such as coded excitation, compressed sensing, and parallel transmission have been proposed, along with image reconstruction methods based on self-supervised deep learning, which have improved the frame rate and image quality of ultrasound imaging. New elastography algorithms have been developed, increasing computational speed by 1-2 orders of magnitude while ensuring high precision. Various new cardiovascular elastography methods have been proposed, including pulse wave imaging, carotid artery elastography, vascular cross-sectional shear wave imaging, myocardial elastography, and cardiac electromechanical wave imaging, which are expected to be used for the early diagnosis and screening of cardiovascular diseases. In collaboration, the first liver transient elastography device in the Asia-Pacific region was developed, with over 4,500 units installed domestically and internationally, covering more than 60 countries/regions, and holding a 70% share of the domestic niche market.
(2) Ultrasound microvascular imaging methods
Research on ultra-fast ultrasound Doppler blood flow imaging, ultrasound brain function imaging, and super-resolution ultrasound imaging has been carried out. A variety of beamforming methods and image processing algorithms have been proposed to improve the resolution, contrast, and signal-to-noise ratio of ultrasound microvascular imaging. Super-resolution ultrasound imaging algorithms based on deep learning have been developed to enhance imaging quality and computational speed.
(3) Intelligent analysis of medical images
An ultrasound image lesion segmentation algorithm based on weakly supervised deep learning has been proposed; disease classification or grading diagnostic algorithms based on radiomics and deep learning have been put forward; an unsupervised deep learning-based multi-label biological microscopic image registration algorithm has been developed, ranking first in both the ANHIR and ACROBAT public datasets.
1. Chen Y, Fang B, Li H, Huang L, Luo J*. Ultrafast online clutter filtering for ultrasound microvascular imaging. IEEE Transactions on Medical Imaging 2025, 44(5): 2477-2491.
2. Wei X, Ge L, Huang L, Luo J*, Xu Y*. Unsupervised non-rigid histological image registration guided by keypoint correspondences based on learnable deep features with iterative training. IEEE Transactions on Medical Imaging 2025, 44(1): 447-461.
3. Ge L, Wei X, Hao Y, Luo J*, Xu Y*. Unsupervised histological image registration using structural feature guided convolutional neural network. IEEE Transactions on Medical Imaging 2022, 41(9): 2414 - 2431.
4. Li Y, Liu Y, Huang L, Wang Z*, Luo J*. Deep weakly-supervised breast tumor segmentation in ultrasound images with explicit anatomical constraints. Medical Image Analysis 2022, 76: 102315.
5. Chen Y, Liu J, Luo X*, Luo J*. ApodNet: Learning for high frame rate synthetic transmit aperture ultrasound imaging. IEEE Transactions on Medical Imaging 2021, 40(11): 3190-3204.
6. Zhang J, He Q, Xiao Y, Zheng H, Wang C*, Luo J*. Ultrasound image reconstruction from plane wave radio-frequency dataset by self-supervised deep neural network. Medical Image Analysis 2021, 70, 102018.
7. Liu X*, Zhou T, Lu M, Yang Y, He Q, Luo J*. Deep learning for ultrasound localization microscopy. IEEE Transactions on Medical Imaging 2020, 39(10): 3064-3078.
8. Liu J, He Q, Luo J*. A compressed sensing strategy for synthetic transmit aperture ultrasound imaging. IEEE Transactions on Medical Imaging 2017, 36(4): 878-891.
9. Zhang G, Pu H, He W, Liu F, Luo J*, Bai J. Bayesian framework based direct reconstruction of fluorescence parametric images. IEEE Transactions on Medical Imaging 2015, 34(6): 1378-1391.
10. Luo J, Konofagou EE. A fast normalized cross-correlation calculation method for motion estimation. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control 2010, 57(6): 1347-1357 (Top 1 cited paper in IEEE TUFFC 2010).
Academic Honors and Awards
2024 IEEE UFFC Editorial Excellence Award
2022 Second-Class Prize of Medical Science and Technology Award, Chinese Medical Science and Technology Award: Key Technological Innovation and Promotion of Non-Invasive Liver Fibrosis Diagnostic System (Ranked 1/9)
2021 Second-Class Prize for Technological Invention, Huang Jiasi Biomedical Engineering Award, Chinese Society of Biomedical Engineering: Non-Invasive Liver Fibrosis Diagnostic System Based on Ultrasound Transient Elastography (Ranked 1/6)
2021 Second-Class Prize for Technological Invention, Chinese Society of Image and Graphics: Non-Invasive Liver Fibrosis Diagnostic System Based on Ultrasound Transient Elastography (Ranked 1/6)
2019 Second-Class Jiangsu Provincial Science and Technology Award: R&D and Industrialization of Image-Guided Non-Invasive Liver Fibrosis Diagnostic System (Ranked 2/6)
2005 Outstanding Doctoral Graduate, Tsinghua University
Courses Taught
Modern Digital Signal Processing
Frontiers and Practice of Medical Imaging
Other Social Positions
Vice Chairman, Instrument Development Professional Committee, Chinese Association of Ultrasound in Medicine and Engineering
Vice Chairman, Medical Ultrasound Engineering Branch, Chinese Society of Biomedical Engineering
Vice Chairman, Medical Imaging and Equipment Professional Committee, Chinese Society of Graphics
Standing Committee Member, Medical Image Information and Control Branch, Chinese Society of Biomedical Engineering
Standing Committee Member, Biomedical Ultrasound Engineering Branch, Acoustical Society of China
Standing Committee Member, Ultrasound Equipment Branch, China Medical Equipment Association
Invention Patents
LUO J, LIU J, HE Q. Method and device for ultrasonic imaging by synthetic focusing. United States Patent. US11307297B2.
LUO Jianwen, LIU Jing, HE Qiong. Synthetic Focusing Ultrasound Imaging Method and Device. Chinese Invention Patent. Patent No.: ZL201510142749.4.
LUO Jianwen, WANG Yuanyuan, HE Qiong, GAO Mengze. A Quantitative Evaluation Method for Ultrasound Images. Chinese Invention Patent. Patent No.: ZL202110117792.0.
LUO Jianwen, WANG Yuanyuan, HE Qiong, GAO Mengze. A Quantitative Evaluation Method for Ultrasound Images. Chinese Invention Patent. Patent No.: ZL202110117779.5.
LUO Jianwen, HUANG Lijie, HE Qiong. A Signal Processing Method and System for Ultrasound Microblood Flow Imaging. Chinese Invention Patent. Patent No.: ZL202210241617.7.
LUO Jianwen, ZHANG Jingke, HE Qiong. Ultrasound Image Reconstruction Method, System, Equipment and Medium. Chinese Invention Patent. Patent No.: ZL202210814598.2.
