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
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
Projects
- 4 Finished
-
The Saint Louis University Component of the NASH Clinical Research Network
12/22/14 → 6/30/15
Project: Federal Funding Agencies
-
(PQD-5) Patient Derived Orthotopic Xenograft Models for Drug Response Prediction
5/15/14 → 4/30/18
Project: Federal Funding Agencies
-
-
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., Jun 21 2023, (E-pub ahead of print) In: Journal of neurointerventional surgery. 16, 3, p. 290-295 6 p.Research output: Contribution to journal › Article › peer-review
3 Scopus citations -
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
6 Scopus citations -
Mrs. Dalloway Said She Would Segment the Chapters Herself
Sui, P., Wang, L., Hamilton, S., Ries, T., Wong, K. & Wong, S. T., 2023, 5th Workshop on Narrative Understanding, WNU 2023 - Proceedings of the Workshop. Akoury, N., Clark, E., Iyyer, M., Chaturvedi, S., Brahman, F. & Chandu, K. R. (eds.). Association for Computational Linguistics (ACL), p. 92-105 14 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
Reliability of the National Institutes of Health (NIH) Stroke Scale Between Emergency Room and Neurology Physicians for Initial Stroke Severity Scoring
Cummock, J. S., Wong, K. K., Volpi, J. J. & Wong, S. T., Apr 2023, In: Cureus. 15, 4, p. e37595Research output: Contribution to journal › Article › peer-review
-
Storyline-Centric Detection of Aphasia and Dysarthria in Stroke Patient Transcripts
Sui, P., Wong, K. K., Yu, X., Volpi, J. J. & Wong, S. T. C., 2023, 5th Workshop on Clinical Natural Language Processing, ClinicalNLP 2023 - Proceedings of the Workshop. Association for Computational Linguistics (ACL), p. 422-432 11 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution