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Zongwei Zhou

College of Health Solutions BM
Grad Teaching Associate
Graduate Assistant/Associate, SCOTTSDALE Campus, Mailcode 9020
Student Information:
Graduate Student
Biomedical Informatics
Health Solutions

Biography: 

Zongwei Zhou is currently a Ph.D. candidate in the Department of Biomedical Informatics, Arizona State University supervised by Dr. Jianming Liang. He has received a B.S. degree with honors in Computer Science from Dalian University of Technology in 2016. He has also spent time at Mayo Clinic, University of California, Berkeley, and Université de Montréal. Drawing upon the realms of biomedical informatics, computer vision, and deep learning, his research focuses on developing novel methodologies to minimize the annotation efforts for computer-aided diagnosis, therapy, and surgery. Zhou has published 10+ peer-reviewed publications in prestigious journals and conferences in his field. Moreover, he holds 3 US patents and additional 7 patents pending. He is the recipient of the MICCAI Young Scientist Award and MedIA Best Paper Award.

Publications: 

Peer-refereed Journal Publications

[1] F. Haghighi, M. R. Hosseinzadeh Taher, Z. Zhou, M. Gotway, J. Liang. "Transferable Visual Word." Submitted to IEEE Transactions on Medical Imaging, 2020.

[2] M. M. Rahman Siddiquee, Z. Zhou, R. Feng, N. Tajbakhsh, M. Gotway, Y. Bengio, and J. Liang. " Fixed-Point Image-to-Image Translation." Submitted to International Journal of Computer Vision, 2020.

[3] Z. Zhou, J. Shin, S. Gurudu, M. Gotway, and J. Liang. "Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts." Submitted to Medical Image Analysis, 2020.

[4] Z. Zhou, V. Sodha, J. Pang, M. Gotway, and J. Liang. "Models Genesis.Medical Image Analysis, 2020. (MedIA Best Paper Award)

[5] Z. Zhou, M. M. Rahman Siddiquee, N. Tajbakhsh, and J. Liang. "UNet++: Redesigning Skip Connections to Exploit Multi-Resolution Features in Image Segmentation.IEEE Transactions on Medical Imaging, 2020. (IEEE TMI most popular articles)

[6] Z. Zhou, J. Shin, R. Feng, R. Hurst, C. Kendall, and J. Liang. "Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation.Journal of Digital Imaging, 2019.

[7] H. Wang, Z. Chen, Z. Zhou, Y. Li, P. Lu, W. Wang, W. Liu, L. Yu. "Evaluation of Machine Learning Classifiers for Diagnosing Mediastinal Lymph Node Metastasis of Lung Cancer from PET/CT Images.Journal of ZheJiang University (Engineering Science), 2018

[8] H. Wang, Z. Zhou, Y. Li, Z. Chen, P. Lu, W. Wang, W. Liu, and L. Yu. "Comparison of Machine Learning Methods for Classifying Mediastinal Lymph Node Metastasis of Non-Small Cell Lung Cancer from 18 F-FDG PET/CT Images.EJNMMI Research, 2017.

 

Peer-refereed Conference Proceedings

[1] R. Feng, Z. Zhou, M. Gotway, J. Liang. "Self-supervised Learning: From Parts to Whole." Domain Adaptation and Representation Transfer (DART’20), 2020.

[2] F. Haghighi, M. R. Hosseinzadeh Taher, Z. Zhou, M. Gotway, J. Liang. "Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration." International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’20), 2020. (Oral)

[3] M. M. Rahman Siddiquee, Z. Zhou, R. Feng, N. Tajbakhsh, M. Gotway, Y. Bengio, and J. Liang. "Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization." International Conference on Computer Vision (ICCV’19), 2019.

[4] Z. Zhou, V. Sodha, M. M. Rahman Siddiquee, R. Feng, N. Tajbakhsh, M. Gotway, and J. Liang. "Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis." International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’19), 2019. (Young Scientist Award; Best Presentation Award Finalist; Oral)

[5] Z. Zhou, M. M. Rahman Siddiquee, N. Tajbakhsh, and J. Liang. "UNet++: A Nested U-Net Architecture for Medical Image Segmentation.Deep Learning in Medical Image Analysis (DLMIA’18), 2018. (Oral)

[6] Z. Zhou, J. Shin, L. Zhang, S. Gurudu, M. Gotway, and J. Liang. "Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally.Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.

 

Conference Abstracts

[1] Z. Zhou, Z. Akkus, M. S. Warner, M. N. Stan, J. Liang, and B. J. Erickson. "A Preliminary Study of Using Machine Learning to Reduce Biopsies of Thyroid Nodules Based on Ultrasound Images.The 2nd SIIM Conference on Machine Intelligence in Medical Imaging, 2017.

[2] P. D. Korfiatis, Z. Zhou, J. Liang, and B. J. Erickson. "Fully Automated IDH Mutation Prediction in MRI Utilizing Deep Learning.The 2nd SIIM Conference on Machine Intelligence in Medical Imaging, 2017.

[3] Z. Zhou, J. Shin, R. T. Hurst, C. B. Kendall, and J. Liang. "Integrating Active Learning and Transfer Learning for Carotid Intima-Media Thickness Video Interpretation.The 2nd SIIM Conference on Machine Intelligence in Medical Imaging, 2017.

[4] L. Zhang, Z. Zhou, H. Siddiki, N. S. Madiraju, F. C. Ramirez, S. R. Gurudu, and J. Liang. "Approaching Medical Fellow-Level Performance on Colonoscopy Frame Classification with Deep Neural Networks.WP Time, the 82rd Annual Meeting, 2017.

Honors / Awards: 
  • Elsevier-MedIA Best Paper Award
  • Sun Award
  • MICCAI Student Participation Award
  • First & third places in Annual Student Poster Competition, BMI/BMD Symposium
  • University Graduate Fellowship, Arizona State University
  • MICCAI Young Scientist Award
  • MICCAI Best Presentation Award Finalist
  • MICCAI Graduate Student Travel Award
  • First place in the Annual Student Poster Competition, Mayo Clinic, BMI/BMD Symposium
  • Outstanding Graduate, Dalian University of Technology
Service: 
  • Journal Reviewer
    • IEEE Transactions on Pattern Analysis and Machine Intelligence
    • Medical Image Analysis
    • IEEE Transactions on Medical Imaging
    • Pattern Recognition
    • IEEE Transactions on Biomedical Engineering
    • Journal of Biomedical and Health Informatics
    • IEEE Access
    • Journal of Biomedical Informatics
  • Conference Area Chair
    • International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’20), Lima, Peru
  • Conference Program Committee
    • AAAI Conference on Artificial Intelligence (AAAI’21), Vancouver, Canada
    • AAAI Conference on Artificial Intelligence (AAAI’20), New York, USA
    • ICCV’19 Workshop Visual Recognition for Medical Images (VRMI), Seoul, Korea
Expertise Areas: