News
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Multi-Contrast MRI Acceleration with K-Space Progressive Learning and Image-Space Self-to-Peer Aggregation
"Multi-Contrast MRI Acceleration with K-Space Progressive Learning and Image-Space Self-to-Peer Aggregation" by Xiaohan Xing, Lequan Yu, Lingting Zhu, Lei Xing, Lianli Liu has been selected as the Best of Physics for this year's ASTRO annual meeting. It will be presented in the oral scientific session "Best of Physics.
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AI Foundation Model (FM)
AI Foundation Model (FM) is coming to medical physics! We are pleased that the work to use FM for automated RT planning is selected as one of "the Best in Physics" at the AAPM 2024 Annual Meeting. Congratulations to Oscar, Sheng, and all co-authors!…
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Cynthia Chuang Honored as AAPM Fellow 2024
Congratulations to Cynthia Chuang for being recognized as an AAPM Fellow in 2024. She will be honored during the 2024 AAPM Annual Meeting in Los Angeles, CA.
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2024 Excellence in Mentoring and Service Award
Ted Graves has been awarded the 2024 Excellence in Mentoring and Service award by the Office of Graduate Education at Stanford. This award recognizes faculty who make distinguished contributions towards enhancing the quality of training and the experiences of Stanford Biosciences graduate students. Congratulations!…
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Large Language Model-Augmented Target Delineation in Radiation Therapy
The work led by Drs. Xianjin Dai and Praveenbalaji Rajendran, focusing on leveraging large language models to extract features from clinical data, which are then incorporated into an auto-delineation method, has been awarded Best in Physics at the AAPM Annual Conference 2024. The manuscript has been accepted for publication in the Red Journal (International Journal of Radiation Oncology, Biology, Physics).