Pew‐Thian Yap
Papers
2
Total Citations
11
H-Index
2
About
Pew-Thian Yap is a leading researcher at the intersection of medical imaging, machine learning, and computational anatomy. His work focuses on developing advanced computational frameworks to enhance surgical guidance and radiation therapy planning. A key contribution is the development of a Bayesian shape framework for localizing the recurrent laryngeal nerve via ultrasound, a technique that promises to reduce nerve damage during thyroid and neck surgeries. This work, published in 2022, has already garnered 6 citations, reflecting its clinical relevance. Yap also pioneered the use of synthetic digital reconstructed radiographs for MR-only robotic stereotactic radiation therapy, a proof-of-concept study from 2021 with 5 citations that aims to eliminate the need for CT scans in certain radiotherapy workflows. His research consistently bridges the gap between algorithmic innovation and practical clinical application, making him a notable figure in precision medicine. Yap’s contributions are particularly impactful for students and researchers interested in how Bayesian methods and synthetic imaging can transform surgical and oncological outcomes.
Research Focus
Key Achievements
Top Papers
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