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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Collaborations and top research areas from the last five years
Projects
- 4 Finished
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The Saint Louis University Component of the NASH Clinical Research Network
Wong, K. (PI)
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
Wong, K. (PI)
5/15/14 → 4/30/18
Project: Federal Funding Agencies
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Advanced MR imaging and spectroscopic tissue characterization in a follow-up study of adjuvant immotheraphy for malignant glioma
Wong, K. (PI)
9/10/08 → 8/31/10
Project: Non Profit
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Automated catheter segmentation and tip detection in cerebral angiography with topology-aware geometric deep learning
Ghosh, R., Wong, K., Zhang, Y. J., Britz, G. W. & Wong, S. T. C., Feb 2024, In: Journal of neurointerventional surgery. 16, 3, p. 290-295 6 p.Research output: Contribution to journal › Article › peer-review
Open Access8 Scopus citations -
Correction: VAM abstracts 2024 - batch 3 - IP001 through IP201 (Journal of Vascular Surgery (2024) 79(6), (S0741521424006414))
Ghosh, R., Wong, K., Yaeger, K. A., Britz, G., Avazmohammadi, R. & Wong, S. T., Oct 2024, In: Journal of Vascular Surgery. 80, 4, p. 1316 1 p.Research output: Contribution to journal › Comment/debate › peer-review
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Frozen Large-scale Pretrained Vision-Language Models are the Effective Foundational Backbone for Multimodal Breast Cancer Prediction
Vo, H. Q., Wang, L., Wong, K., Ezeana, C. F., Yu, X., Yang, W., Chang, J. C., Nguyen, H. V. & Wong, S. T., 2024, In: IEEE Journal of Biomedical and Health Informatics. 29, 5, p. 1-14 14 p.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
M3 Stroke: Multi-Modal Mobile AI for Emergency Triage of Mild to Moderate Acute Strokes
Cai, T., Wong, K., Wang, J. Z., Huang, S., Yu, X., Volpi, J. J. & Wong, S. T. C., 2024, BHI 2024 - IEEE-EMBS International Conference on Biomedical and Health Informatics, Proceedings. Institute of Electrical and Electronics Engineers Inc., (BHI 2024 - IEEE-EMBS International Conference on Biomedical and Health Informatics, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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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., Jul 2023, In: Computerized Medical Imaging and Graphics. 107, p. 102236 102236.Research output: Contribution to journal › Article › peer-review
10 Scopus citations