返回
Wuwei Ren
Assistant Professor
Graduated School: ETH Zurich, Switzerland
Tel: 021-20684434
Office: 1D-401.A
Homepage: http://miblab.sist.shanghaitech.edu.cn/
Research Area:
Affiliation:
Research Group:
Research Area: Optical Imaging, Image reconstruction, Multimodal imaging
招聘主页：
Profile
Teammate
Research
Educate
Service
achievements
Papers
Videos
Related
Main Responsibilities(A)
Minor Responsibilities(B)
Minor Responsibilities(C)

Dr. Wuwei Ren received his bachelor, master, and PhD degrees from Zhejiang University China (2010), KTH Sweden (2012), and ETH Zurich Switzerland (2018), respectively. Dr. Ren received his postdoctoral training at University of Zurich, Switzerland. He was also a visiting scholar at University College London, UK. Currently, Dr. Ren serves as a tenure-track assistant professor at ShanghaiTech University. He was awarded STINT scholarship by the Swedish government, the Swiss Innovation and Technology Agency BRIDGE Fellowship, and SNF Project Fund. In 2020, he was awarded the ‘Shanghai Youth Eastern Scholar’ Title. His work has been published in top journals such as IEEE TBME, Light, OE, BOE, JBP, Inv Prob & Img, Neurophotonics, etc. He has been actively organizing the European Molecular Imaging Meetings (EMIMs) and serving as a sub-category chair in EMIM2020 and a category chair in EMIM2021. His optical imaging prototype has won several European entrepreneurial awards including VentureKick award and displayed in Swiss Innovation Pavilion, Hannover Messe 2019. His work in system and software development has led to a PCT patent. Now he is the head of The Molecular Imaging and Biophotonics Laboratory with the aim of pioneering next-generation medical imaging tools for early diagnostics, drug development, and image-guided surgery.


Education

2012-2018      PhD in Biomedical Engineering, ETH Zurich, Switzerland

2010-2012      M. S. in Medical imaging, Royal Institute of Technology KTH, Sweden

2006-2010      B. S. in Biomedical Engineering, Zhejiang University, China

 

Experience

2020.9-now                Assistant Professor, ShanghaiTech University, China

2020.1-2020.9            Postdoc Researcher, ETH Zurich, Switzerland

2018.8-2020.1            BRIDGE Fellow, University Hospital Zurich, Switzerland

2016.7-2016.8            Visiting Scholar, University College London, UK

 

Research Interests

Optical imaging (Fluorescence imaging, Optoacoustic imaging, Diffuse optical imaging, etc.)

Optical simulation, Image reconstruction & Image processing

Multimodal imaging, specialized in MRI-optics hybrid systems

Image-guided surgery & Preclinical imaging

 

Professional Societies

Category Chair, European Molecular Imaging Meeting (EMIM), 2021, 2020

Member of ESMI, OSA, and SPIE

President & co-founder, Swiss-Sino Medical Technology Association, 2016-2020


Honors & Awards

Shanghai Oriental Professorship, Shanghai, 2020-2023

BRIDGE fellowship, Swiss National Science Foundation, 2018-2020

Biophotonics congress travel award, OSA, 2019

STINT scholarship for academic excellence, Swedish government, 2010-2012

Outstanding student leadership award, Zhejiang University, 2010



  • Name：Liang Chen
    Position：Engineer
    Duration：
    Email：
  • Name：Linlin Li
    Position：PhD student
    Duration：
    Email：
  • Name：Yexing Hu
    Position：Master student
    Duration：
    Email：
  • Name：Xinyi Zhu
    Position：Master student
    Duration：
    Email：
  • Name：Chen Duan
    Position：Master student
    Duration：
    Email：
  • Name：Jianru Zhang
    Position：Master student
    Duration：
    Email：
  • Name：Yanan Wu
    Position：Master student
    Duration：
    Email：
  • Name：Shihan Zhao
    Position：Master student
    Duration：
    Email：
  • Name：Kaiqi Kuang
    Position：Master student
    Duration：
    Email：
  • Name：Liangtao Gu
    Position：Master student
    Duration：
    Email：

Direction 1: Multi-contrast optical imaging platform

Description: We are aiming at developing a novel optical imaging platform capable of visualizing multiple contrast parameters in biological tissues. The platform integrates the state-of-the-art hardware components such as wavelength-tunable pulse laser and time-of-flight cameras, as well as novel reconstruction algorithms and accurate calibration methods. Main application of such a platform includes small animal imaging and image-guided surgery.

Reference:

1.     W. Ren, J. Jiang, A. D. Costanzo Mata, A. Kalyanov, J. Ripoll, S. Lindner, E. Charbon, C. Zhang, M. Rudin, and M. Wolf, Multimodal imaging combining time-domain near-infrared optical tomography and continuous-wave fluorescence molecular tomography, Opt Express 28, 9860-9874 (2020).

2.     W. Ren, H. Isler, M. Wolf, J. Ripoll, and M. Rudin, Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation, IEEE Trans Biomed Eng 67, 16-26 (2020).

3.     W. Ren, L. Li, J. Zhang, M. Vaas, J. Klohs, J. Ripoll, M. Wolf, R. Ni, and M. Rudin, Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography, Biomed Opt Express 13, 3809-3822 (2022).

  




Direction 2: Optics-MRI hybrid system

Description: Multimodal imaging has emerged as a powerful method for biomedical research and clinical usage, as more comprehensive physiological information can be achieved compared with a standalone modality. In our lab, we combine optics and MRI due to several reasons. First, optical imaging, fluorescence imaging in particular, features high sensitivity and specificity which is complementary to MRI. Second, MRI can provides as an accurate anatomical reference that is useful for localizing the fluorescence signal. Third, both MRI and optical imaging can avoid ionizing radiation. Our team has previously developed the world’s first fluorescence tomography-MRI system and optoacoustic tomography-MRI system. 

Reference: 

1.     W. Ren, X. L. Dean-Ben, M. A. Augath, and D. Razansky, Development of concurrent magnetic resonance imaging and volumetric optoacoustic tomography: A phantom feasibility study, J Biophotonics 14, e202000293 (2021).

2.     Y. Hu, B. Lafci, A. Luzgin, H. Wang, J. Klohs, X. L. Dean-Ben, R. Ni, D. Razansky, and W. Ren, Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging, Biomed Opt Express 13, 4817-4833 (2022).

3.     W. Ren, B. Ji, Y. Guan, L. Cao, and R. Ni, Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics, Front Med (Lausanne) 9, 771982 (2022).

  



Direction 3: AI-empowered image reconstruction

Description: The conception of 3D reconstruction is commonly used in optical microscopy, e.g., in confocal microscopy and two-photon microscopy. However, visualizing objects deeply seated in tissue (> 1 mm) becomes challenging due to severe light scattering in tissue. Such a macroscopic reconstruction in scattering media is well known as a highly ill-posed inverse problem. We are seeking for fast, robust, 3D, high-resolution image reconstruction algorithms based on advanced computational techniques and novel machine learning methods. 

Reference: 

1.     Y. Liu, W. Ren, and H. Ammari, Robust reconstruction of fluorescence molecular tomography with an optimized illumination pattern, Inverse Problems & Imaging 14, 535-568 (2020).

2.     W. Ren, H. Isler, M. Wolf, J. Ripoll, and M. Rudin, Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation, IEEE Trans Biomed Eng 67, 16-26 (2020).

  



  • Digital Signal Processing, ShanghaiTech-EE152, 2021 Spring, 2022 Spring, 2023 Spring

  • Digital Image Processing, ShanghaiTech-CS270, 2021 Fall, 2022 Fall

  • Multi-modal Brain-Computer Interface: Algorithms and Systems, ShanghaiTech-SI361, 2021 Spring, 2022 Spring


Journal papers: 

  1. Zhu X, Gu L, Li R, Chen L, Chen, J, Zhou N*, Ren W* (2023), MiniMounter: a low‐cost miniaturized microscopy development toolkit for image quality control and enhancement. Journal of Biophotonics, e202300214

  2. Gao S, Zhang J, Hu Y, Wu Y, Li L, Hu Q, Lou X, Zhu X, Jiang J*, Ren W* (2023), Multifunctional Optical Tomography System with High-fidelity Surface Extraction based on a Single Programmable Scanner and Unified Pinhole Modeling, IEEE Transactions on Biomedical Engineering, 1-13

  3. Ren W, Dean-Ben Xl, Skachokova Z, Augath M, Ni R, Chen Z, Razansky D* (2023) Monitoring mouse brain perfusion with hybrid magnetic resonance optoacoustic tomography. Biomed Opt Express 14: 1192-1204

  4. Ren W*, Li L, Zhang J, Vaas M, Klohs J, Ripoll J, Wolf M, Ni R, Rudin M (2022) Non-invasive visualization of amyloid-beta deposits in Alzheimer amyloidosis mice using magnetic resonance imaging and fluorescence molecular tomography. Biomed Opt Express 13: 3809-3822

  5. Ren W*, Ji B, Guan Y, Cao L, Ni R* (2022) Recent Technical Advances in Accelerating the Clinical Translation of Small Animal Brain Imaging: Hybrid Imaging, Deep Learning, and Transcriptomics. Front Med (Lausanne) 9: 771982

  6. Hu Y, Lafci B, Luzgin A, Wang H, Klohs J, Dean-Ben XL, Ni R, Razansky D*, Ren W*(2022) Deep learning facilitates fully automated brain image registration of optoacoustic tomography and magnetic resonance imaging. Biomed Opt Express 13: 4817-4833

  7. Chen Z, Gezginer I, Augath MA, Ren W, Liu YH, Ni R, Dean-Ben XL, Razansky D* (2022) Hybrid magnetic resonance and optoacoustic tomography (MROT) for preclinical neuroimaging. Light Sci Appl 11: 332

  8. Zhou R, Ji B, Kong Y, Qin L, Ren W, Guan Y, Ni R* (2021) PET Imaging of Neuroinflammation in Alzheimer's Disease. Front Immunol 12: 739130

  9. Ren W, Dean-Ben XL, Augath MA, Razansky D* (2021) Development of concurrent magnetic resonance imaging and volumetric optoacoustic tomography: A phantom feasibility study. J Biophotonics 14: e202000293

  10. Ren W, Cui S, Alini M, Grad S, Zhou Q, Li Z, Razansky D* (2021) Noninvasive multimodal fluorescence and magnetic resonance imaging of whole-organ intervertebral discs. Biomed Opt Express 12: 3214-3227

  11. Ren W*, Jiang J, Costanzo Mata AD, Kalyanov A, Ripoll J, Lindner S, Charbon E, Zhang C, Rudin M, Wolf M (2020) Multimodal imaging combining time-domain near-infrared optical tomography and continuous-wave fluorescence molecular tomography. Opt Express 28: 9860-9874

  12. Ren W, Isler H, Wolf M, Ripoll J, Rudin M* (2020) Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation. IEEE Trans Biomed Eng 67: 16-26

  13. Liu Y, Ren W*, Ammari H (2020) Robust reconstruction of fluorescence molecular tomography with an optimized illumination pattern. Inverse Problems & Imaging 14: 535-568

  14. Ren W, Skulason H, Schlegel F, Rudin M, Klohs J, Ni R* (2019) Automated registration of magnetic resonance imaging and optoacoustic tomography data for experimental studies. Neurophotonics 6: 025001

  15. Ni R, Vaas M, Ren W, Klohs J* (2018) Noninvasive detection of acute cerebral hypoxia and subsequent matrix-metalloproteinase activity in a mouse model of cerebral ischemia using multispectral-optoacoustic-tomography. Neurophotonics 5: 015005

  16. Ren W, Elmer A, Buehlmann D, Augath M-A, Vats D, Ripoll J, Rudin M* (2016) Dynamic Measurement of Tumor Vascular Permeability and Perfusion using a Hybrid System for Simultaneous Magnetic Resonance and Fluorescence Imaging. Mol Imaging Biol 18: 191-200

 

Proceeding papers:

  1. Hu Y, Lafci B, Luzgin A, Wang H, Klohs J, Dean-Ben XL, Ni R, Razansky D, Ren W* (2022) Automatic image registration of optoacoustic tomography and magnetic resonance imaging based on deep learning. Proc. SPIE, First Conference on Biomedical Photonics and Cross-Fusion, 1246103, doi: doi.org/10.1117/12.2655214

  2. Ren W, Dean-Ben XL, Augath M, Razansky D* (2021) Feasibility study on concurrent optoacoustic tomography and magnetic resonance imaging. Proc. SPIE, doi: (oral & Best Paper Nomination in SPIE Photonics West,  ranking top 5%)

  3. Ren W*, Jiang J, Di Costanzo MA, Kalyanov A, Ripoll J, Lindner S, Charbon S, Zhang C, Rudin M, Wolf M (2020) Time-domain Near Infrared Optical Tomography Guided Fluorescence Molecular Tomography, Biophotonics Congress: Biomedical Optic. OSA

  4. Jiang J, Ren W, Isler H,  Kalyanov A, Lindner S, Mata Aldo D. C, Rudin M, Wolf M* (2020), Validation and Comparison of Monte Carlo and Finite Element Method in Forward Modeling for Near Infrared Optical Tomography. In Oxygen Transport to Tissue XLI (pp. 307-313). Springer, Charm

  5. Polatoglu M N, Liu Y, Ni R, Ripoll J, Rudin M, Wolf M, Ren W* (2019), Simulation of fluorescence molecular tomography using a registered digital mouse atlas, Proc. SPIE, doi: /10.1117/12.2525366

  6. Ren W, Skulason H, Schlegel F, Rudin M, Klohs J, Ni R* (2019), Automated registration for optoacoustic tomography and MRI, In Optical Molecular Probes, Imaging and Drug Delivery. OSA

  7. Ni R, Vaas M, Ren W, Klohs J* (2018), Non-invasive detection of matrix-metalloproteinase activity in a mouse model of cerebral ischemia using multispectral optoacoustic tomography, Proc. SPIE, doi: 10.1117/12.2286313

  8. Ren W, Elmer A, Augath M, Rudin M* (2016), FEM-based Simulation of a Fluorescence Tomography Experiment using Anatomical MR Images, Proc. SPIE, doi:10.1117/12.2216454

  9. Ren W, Valastyán I, Colarieti-Tosti M* (2012), Stationary SPECT with multi-layer Multiple-Pinhole-Arrays, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), doi: 10.1109/NSSMIC.2012.6551593 

  10. Valastyán I*, Colarieti-Tostia M, Ren W, Turco, A, Kereka A (2012), Monte Carlo simulation of a dental Positron Emission Tomograph and image reconstruction of scatter and true coincidence events, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), doi: 10.1109/NSSMIC.2012.6551795

 

Patent:

  1. Ren W, Rudin M, Method for selecting an illumination pattern for a fluorescence molecular tomography measurement, (PCT/EP2020/051779)

  2. 任无畏，高圣宇，吴亚男，连续波光源非接触式的光学断层扫描系统及扫描方法(CN202210859035.5)