Junyu's Curriculum Vitae

My CV (Updated 10/05/2023)

Education

• B.Sc. in Computer Engineering, Summa Cum Laude, North Carolina State University, 2017
• B.Sc. in Electrical Engineering, Summa Cum Laude, North Carolina State University, 2017
• M.S.E. in Electrical & Computer Engineering, Johns Hopkins University, 2019
• Ph.D. in Electrical & Computer Engineering, Johns Hopkins University, 2022

Professional experience

• Jan 2023 - Present: Research Associate (Faculty)
  • Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD
  • Duties included:
    • Nuclear Medicine imaging
    • Medical Image Analysis
    • Deep Learning
  • Supervisor: Dr. Yong Du
• Sep 2017 - Dec 2022: Graduate Research Assistant
  • Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, Baltimore, MD
  • Duties included:
    • Nuclear Medicine imaging
    • NM image segmentation
    • NM image denoising
    • Quantitative accuracy
  • Supervisor: Dr. Eric C. Frey
• Jun 2020 - Oct 2021: PET Image Reconstruction and Quality Scientist Intern
  • Canon Medical Research USA, Inc., Vernon Hills, IL
  • Duties included:
    • PET image denoising
    • Transfer learning
    • Domain adaptation for deep neural networks
  • Mentor & Supervisor: Dr. Chung (Jan) Chan & Dr. Evren Asma
• May 2016 – Jul 2017: Unergraduate Research Assistant
  • North Carolina State University, Raleigh, NC
  • Duties included:
    • Real time ECG peak detection
    • Adaptive filter design for ECG signals
  • Supervisor: Dr. Edgar Lobaton
• Aug 2016 – Dec 2016: Undergraduate Research Fellow
  • The NSF Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies, Raleigh, NC
  • Duties included:
    • Peak Detection Algorithm testing for ECG signals.
    • QRS-Wave Detection, P-Wave Detection, Heart Rate estimation
• Jun 2015 – Aug 2015: Application Engineer Intern
  • Analog Devices, Inc., Greensboro, NC
  • Duties included:
    • RF, Wireless Communication System
    • Worked with Wireless Communication Group.
    • Did several performance measurements for their transceiver products.
  • Supervisor: Kenny Man

Journal peer review activities

Junyu Chen on Publons

1. Medical Physics (IF: 4.506) - Reviewer Certificate (2021)
2. Computer Methods and Programs in Biomedicine (IF: 5.428)
3. IEEE Access (IF: 3.476)
4. Quantitative Imaging in Medicine and Surgery (IF: 4.630)
5. IEEE Transactions on Medical Imaging (IF: 11.037)
6. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (IF: 3.267)
7. IEEE Transactions on Radiation and Plasma Medical Sciences
8. IEEE Journal of Biomedical and Health Informatics (IF: 7.021)
9. Medical & Biological Engineering & Computing (IF: 3.079)
10. Medical Image Analysis (IF: 13.83)
11. European Radiology (IF: 5.9)
12. Pattern Recognition (IF: 8)
13. Nature Biomedical Engineering (IF: 28.1)
14. IEEE Transactions on Image Processing (IF: 10.6)

Conference peer review activities

1. Medical Imaging with Deep Learning (MIDL) 2022
2. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022

Teaching experience

• Aug 2022 - Dec 2022: Teaching Assistant
  • Medical Imaging Systems (EN520.432/EN580.472/EN520.632), Johns Hopkins University, Baltimore, MD
• Aug 2021 - Dec 2021: Teaching Assistant
  • Medical Imaging Systems (EN520.432/EN580.472/EN520.632), Johns Hopkins University, Baltimore, MD
• Aug 2020 - Dec 2020: Teaching Assistant
  • Medical Imaging Systems (EN520.432/EN580.472/EN520.632), Johns Hopkins University, Baltimore, MD
• Aug 2019 - Dec 2019: Teaching Assistant
  • Medical Imaging Systems (EN520.432/EN580.472/EN520.632), Johns Hopkins University, Baltimore, MD
• Jan 2019 - May 2019: Course Assistant
  • Medical Image Analysis (EN520.433/623), Johns Hopkins University, Baltimore, MD
• Jan 2017 - May 2017: Teaching Assistant
  • Electric Circuits (ECE 211), North Carolina State University, Raleigh, NC

Peer-reviewed publications

Junyu Chen on Google Scholar

Journal Preprints:

1. Chen, J., Liu, Y., He, Y., & Du, Y. (2023). Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration. arXiv preprint arXiv:2303.06168.
2. Liu, Y., Chen, J., Zuo, L., Du, Y., Carass, A., & Prince, J. L. (2023). Vector Field Attention for Deformable Image Registration. (Submitted to IEEE Transactions on Medical Imaging)
3. Chen, J.*, Liu, Y.*, Wei, S.*, Bian, Z., Subramanian, S., Carass, A., Prince, J. L., & Du, Y. (2023). A Survey on Deep Learning in Medical Image Registration: New Technologies, Uncertainty, Evaluation Metrics, and Beyond. arXiv preprint arXiv:2307.15615. (*: Equal contributions; Submitted to Medical Image Analysis)

Journal Publications:

1. Li, Y., Zhao, L., Amindarolzarbi, A., Mena, E., Leal, J., Chen, J., …, Bai, H. X. (2024). An Automated Deep Learning-based Framework for Uptake Segmentation and Classification on PSMA PET/CT/ Imaging of Patients with Prostate Cancer. Journal of Imaging Informatics in Medicine.
2. Liu, Y., Chen, J., Wei, S., Carass, A., & Prince, J.L. (2024). On Finite Difference Jacobian Computation in Deformable Image Registration. International Journal of Computer Vision.
3. Jang, S. I., Pan, T., Li, Y., Heidari, P., Chen, J., Li, Q., & Gong, K. (2023). Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising. IEEE Transactions on Medical Imaging.
4. Li, Y., Chen, J., Jang, S. I., Gong, K., & Li, Q. (2023). SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images. Medical Physics.
5. Li, Y., Brown, J., Xu, J., Chen, J., Ghaly, M., Dugan, M., Cao, X., Du, Y., Fahey, F. H., Bolch, W., Sgouros, G., & Frey E. F. (2023). Girth-based Administered Activity for Pediatric 99mTc-DMSA SPECT. Medical Physics.
6. Li, J.*, Chen, J. *(Co-first author), Tang, Y.*, Wang, C., Landman, B. A., & Zhou, S. K. (2023). Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives. Medical Image Analysis, 102762. (*: Equal contributions)
7. Chen, J., Frey, E. C., He, Y., Segars, W. P., Li, Y., & Du, Y. (2022). Transmorph: Transformer for unsupervised medical image registration. Medical Image Analysis, 102615.
8. Chen, J., Li, Y., Luna, L. P., Chung, H. W., Rowe, S. P., Du, Y., Solnes, L. B., & Frey, E. C. (2021). Learning fuzzy clustering for SPECT/CT segmentation via convolutional neural networks. Medical physics, 48(7), 3860-3877.
9. Li, Y., Chen, J., Brown, J. L., Treves, S. T., Cao, X., Fahey, F. H., … & Frey, E. C. (2021). DeepAMO: a multi-slice, multi-view anthropomorphic model observer for visual detection tasks performed on volume images. Journal of Medical Imaging, 8(4), 041204.
10. Chen, J., Li, Y., Du, Y., & Frey, E. C. (2020). Generating Anthropomorphic Phantoms Using Fully Unsupervised Deformable Image Registration with Convolutional Neural Networks. Medical Physics, 47: 6366-6380. (Editor’s Choice)

Conference Publications:

1. Chen, J., Liu, Y., He, Y., & Du, Y. (2023). Deformable Cross-Attention Transformer for Medical Image Registration. In Machine Learning in Medical Imaging (MLMI). (Oral Presentation)
2. Chen, J., Frey, E. C., & Du, Y. (2022). Unsupervised Learning of Diffeomorphic Image Registration via TransMorph. In International Workshop on Biomedical Image Registration (WBIR). (Long oral presentation)
3. Li, Y., Cui, J., Chen, J., Zeng, G., Wollenweber, S., Jansen, F., … & Li, Q. (2022). A Noise-level-aware Framework for PET Image Denoising. In International Workshop on Machine Learning for Medical Image Reconstruction. Springer, Cham.
4. Chen, J., Asma, E., & Chan, C. (2021). Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-tuning and Online-learning. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). (Oral presentation, provisionally accepted, top 13% of 1630 papers)
5. Chen, J., He, Y., Frey, E. C., Li, Y., & Du, Y. (2021). ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration. In Medical Imaging with Deep Learning (MIDL).
6. Chen, J., Li, Y., Du, Y., & Frey, E. (2021). Creating Anthropomorphic Phantoms via Unsupervised Convolutional Neural Networks. In Medical Imaging with Deep Learning (MIDL).
7. Chen, J., & Frey, E. C. (2020, January). Medical Image Segmentation via Unsupervised Convolutional Neural Network. In Medical Imaging with Deep Learning (MIDL).
8. Chen, J., Jha, A. L., & Frey, E. C. (2019). Incorporating CT prior information in the robust fuzzy C-means algorithm for QSPECT image segmentation. Proc. SPIE 10949, Medical Imaging 2019: Image Processing.
9. Li, X., Yang, F., Cheng, H., Chen, J., Guo, Y., & Chen, L. (2017, October). Multi-scale cascade network for salient object detection. In Proceedings of the 25th ACM international conference on Multimedia (pp. 439-447).
10. Li, X., Chen, L., & Chen, J. (2017, December). A visual saliency-based method for automatic lung regions extraction in chest radiographs. In 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) (pp. 162-165). IEEE.
11. Zhong, B., Qin, Z., Yang, S., Chen, J., Mudrick, N., Taub, M., … & Lobaton, E. (2017, December). Emotion recognition with facial expressions and physiological signals. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-8). IEEE.

Abstract Publications

1. Li, Y., Brown, J., Xu, J., Chen, J., Ghaly, M., Cao, X., Du, Y., Fahey, F., Bolch, W., Sgouros, G., & Frey, E. (2022). Justification for and In Silico Evaluation of a New Local-body-morphometry Based Dosing Method for Pediatric 99mTc-DMSA SPECT. Journal of Nuclear Medicine 63 (supplement 1).
2. Jang, S., Pan, T., Li, Y., Chen, J., Li, Q., & Gong, K. (2022). PET image denoising based on transformer: evaluations on datasets of multiple tracers. Journal of Nuclear Medicine 63 (supplement 1).
3. Chen, J., Frey, E., & Du, Y. (2022). Class-incremental learning for multi-organ segmentation. Journal of Nuclear Medicine 63 (supplement 1). (Oral presentation)
4. Chen, J., Li, Y., Du, Y., Luna, L., Rowe, S., & Frey, E. (2021). Semi-supervised SPECT segmentation using convolutional neural networks. Journal of Nuclear Medicine 62 (supplement 1), 1423-1423.
5. Chen, J., Li, Y., & Frey, E. (2020). A fully unsupervised approach to create patient-like phantoms via convolutional neural networks. Journal of Nuclear Medicine, 61(supplement 1), 522-522. (Oral presentation)
6. Li, Y., Chen, J., Brown, J., Treves, S. T., Cao, X., Fahey, F., … & Frey, E. (2020). DeepAMO: An Anthropomorphic Model Observer for Visual Detection Tasks in Volume Images. Journal of Nuclear Medicine, 61(supplement 1), 1427-1427.
7. Chen, J., Frey, E. C., & Lodge, M. A. (2019). Accuracy of PET/CT quantification in bone. Journal of Nuclear Medicine 60 (supplement 1), 1201-1201.

Memberships

• Society of Nuclear Medicine and Molecular Imaging (SNMMI), Member
• Institute of Electrical and Electronics Engineers (IEEE), Member
• The International Society for Optics and Photonics (SPIE), Student Member
• Association for Computing Machinery (ACM), Student Member
• The Medical Image Computing and Computer Assisted Intervention Society (MICCAI), Member

Awards & Honors

1. Fully Funded Graduate Assistantship, Radiological Physics Division, Johns Hopkins Medical Institute (2019 – 2022)
2. SNMMI Student Research Grant Award: Discovering Molecular Imaging (2022)
3. 2023 Johns Hopkins Discovery Award
4. 2023 IEEE NSS MIC RTSD Trainee Grant
5. 2024 Forbes 30 Under 30 in Healthcare Link

TEACHING

I gave several guest lectures when I was a TA for Medical Imaging Systems course, some lecture recordings can be found here:

• Physics of Nuclear Medicine