Authors: Wenbo Gu, Chenhui Qiu, Ke Sheng, Liyan Sun, Weiyuan Sun, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiology, Stanford University, University of Pennsylvania, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, Stanford University,
Abstract Preview: Purpose:
The small animal radio-neuromodulation platform developed in our previous work utilized focused kV x-ray beams rotating and translating in predefined trajectories to irradiate small, mm si...
Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap
Affiliation: University of North Carolina at Chapel Hill, Huaqiao University
Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...
Authors: Amar Kishan, Jun Lian, Yunkui Pang, Jonathan Pham, X. Sharon Qi, Michael Steinberg, Luca F Valle, Pew-Thian Yap
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of North Carolina at Chapel Hill
Abstract Preview: Purpose: Stereotactic body radiotherapy (SBRT) is a highly effective treatment for prostate cancer, yet predicting genitourinary (GU) toxicity has primarily relied on planned dosimetry. This study inv...
Authors: Maria Jose Medrano, Grant Stevens, Liyan Sun, Justin Ruey Tse, Adam S. Wang, Sen Wang
Affiliation: Department of Radiology, Stanford University, GE HealthCare, Stanford University
Abstract Preview: Purpose: Patient exposure to ionizing radiation is a major concern in CT imaging. Size-specific dose estimation methods can prospectively estimate organ-level radiation doses based on patient sizes an...
Authors: Liyuan Chen, Sepeadeh Radpour, David Sher, Jing Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Accurate lymph node malignancy prediction is pivotal in optimizing radiation treatment strategies for head and neck (HN) cancer patients. While conventional radiomics models leverage intensit...