Projects per year
Personal profile
Personal profile
Dr. Wong is a biomedical engineer who specializes in developing new imaging systems and methods for the visualization of human disease. He received his Magnetic Resonance (MR) physics training at Columbia University in New York City, and in 2005, he joined the Functional and Molecular Imaging Center of the Brigham and Women’s Hospital and the HCNR Center of Bioinformatics in the Harvard Medical School as a Postdoctoral Fellow. In 2007, he joined the Houston Methodist Research Institute and is a faculty member of Weill Cornell Medicine since 2008.
Research interests
Dr. Wong’s current research interests focus on machine learning and deep learning in medical imaging. He is a Director of neuroimaging at TT and WF Chao Center for BRAIN for neurological disorders. His laboratory specialized in using deep learning derived features in addition to clinical features from electronic medical records for outcome prediction. Some examples include deep genomic features for glioblastoma patient survival modeling, deep imaging features for stroke patient outcome modeling.
Education/Academic qualification
Bioinformatics, Postdoctoral Fellowship, Harvard University
Electrical & Electronic Engineering, M Phil, University of Hong Kong
Electrical & Electronic Engineering, PhD, University of Hong Kong
Research Area Keywords
- Systems Medicine & Bioinformatics
- Cancer
Free-text keywords
- Cancer imaging
- Image-guided intervention
- Molecular imaging
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Projects
- 4 Finished
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The Saint Louis University Component of the NASH Clinical Research Network
12/22/14 → 6/30/15
Project: Federal Funding Agencies
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(PQD-5) Patient Derived Orthotopic Xenograft Models for Drug Response Prediction
5/15/14 → 4/30/18
Project: Federal Funding Agencies
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BBox-Guided Segmentor: Leveraging expert knowledge for accurate stroke lesion segmentation using weakly supervised bounding box prior
Ou, Y., Huang, S. X., Wong, K. K., Cummock, J., Volpi, J., Wang, J. Z. & Wong, S. T. C., Jul 2023, In: Computerized Medical Imaging and Graphics. 107, 102236.Research output: Contribution to journal › Article › peer-review
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Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-contrast CT Scans
Ni, H., Xue, Y., Wong, K., Volpi, J., Wong, S. T. C., Wang, J. Z. & Huang, X., Sep 16 2022, (E-pub ahead of print) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings. Wang, L., Dou, Q., Fletcher, P. T., Speidel, S. & Li, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 416-426 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13438 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Other chapter contribution
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A Time-Series Feature-Based Recursive Classification Model to Optimize Treatment Strategies for Improving Outcomes and Resource Allocations of COVID-19 Patients
Wang, L., Yin, Z., Puppala, M., Ezeana, C., Wong, K., He, T., Gotur, D. & Wong, S., Jul 1 2022, In: IEEE Journal of Biomedical and Health Informatics. 26, 7, p. 3323-3329 7 p.Research output: Contribution to journal › Article › peer-review
Open Access3 Scopus citations -
Automatic Segmentation in Acute Ischemic Stroke: Prognostic Significance of Topological Stroke Volumes on Stroke Outcome
Wong, K. K., Cummock, J. S., Li, G., Ghosh, R., Xu, P., Volpi, J. J. & Wong, S. T. C., Sep 1 2022, In: Stroke. 53, 9, p. 2896-2905 10 p.Research output: Contribution to journal › Article › peer-review
4 Scopus citations -
DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning
Cai, T., Ni, H., Yu, M., Huang, X., Wong, K., Volpi, J., Wang, J. Z. & Wong, S. T. C., Aug 2022, In: Medical Image Analysis. 80, 102522.Research output: Contribution to journal › Article › peer-review
1 Scopus citations