Search Submissions 🔎

Results for "Xianjin Dai, PhD": 8 found

A Hybrid 4π-Proton Arc Robust Optimization

Authors: Wenhua Cao, Xianjin Dai, PhD, Hadis Moazami Goudarzi, Gino Lim, Miaolan Xie, Lei Xing, Lewei Zhao

Affiliation: University of Chicago Booth School of Business, Department of Radiation Oncology, Stanford University, Department of Industrial Engineering, University of Houston, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: Proton Arc Therapy (PAT) delivers a continuous dose of radiation during gantry rotation. 4π is a non-coplanar technique used for advanced proton therapy delivery. This work proposes a hybrid ...

BEST IN PHYSICS MULTI-DISCIPLINARY: Foundation Model-Empowered Unsupervised 3D Deformable Medical Image Registration

Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, Stanford University, Duke University, Stanford University

Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...

Evaluating Tumor Shrinkage Using Fractionated Radiotherapy: A Mixed Finite Element Method (FEM) for Free Boundary Problem

Authors: Xianjin Dai, PhD, Xiang Wan, Lei Xing, Qiuyun Xu, Lewei Zhao, Zeyu Zhou

Affiliation: Department of Radiation Oncology, Stanford University, Carl Zeiss X-ray Microscopy, Department of Mathematics and Statistics, Loyola University Chicago, Department of Radiation Oncology, City of Hope National Medical Center

Abstract Preview: Purpose: The purpose of this study is to examine and quantify tumor shrinkage over time in response to fractionated radiotherapy. We seek to establish a predictive model that can provide a systematic ...

Foundation Model-Augmented Learning for Automatic Delineation in Precision Radiotherapy

Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...

Image Quality Enhancement for Transrectal Ultrasound Imaging of Prostate Brachytherapy Using Deep Learning: A Needle Eraser

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Serdar Charyyev, Xianjin Dai, PhD, Yu Gao, Thomas R. Niedermayr, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Real-time transrectal ultrasound imaging is the gold standard for needle placement and treatment planning of real-time based-ultrasound-based high dose-rate (HDR) prostate brachytherapy. Cumu...

Leveraging Hybrid Quantum Solvers for Eye Plaque Brachytherapy Treatment Planning Optimization

Authors: Xianjin Dai, PhD, Wu Liu, Eric Nguyen, Lei Xing, Lewei Zhao

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Recent developments in hybrid quantum solvers, which combine quantum and classical processing, enable greater flexibility to tackle problems outside the limited scope of pure quantum computin...

Precision Radiotherapy Dose Prediction Using Foundation Model-Augmented Learning

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Xianjin Dai, PhD, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Artificial intelligence (AI)-driven methods have transformed dose prediction, streamlining the automation of radiotherapy treatment planning. However, traditional approaches depend exclusivel...

Recent Advances in AI-Segmentation for Radiation Therapy

Authors: Xianjin Dai, PhD

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: N/A...