Stanford researchers in the Xing Lab have developed GPT-RadPlan, a large language model (LLM) and vision-language model (VLM) based radiation therapy treatment planning automation tool that reduces treatment planning time and lowers costs.
Researchers at Stanford have developed, for the first time, a component analysis algorithm that does not require any assumption on the data structure or data generation process to find out the important components or trends in data.
Stanford researchers have developed a novel and efficient method for generating real-time 3D volumetric computed tomography (CT) images with 2D single or few-view projections, instead of several hundreds of projections as required in existing CT imaging system.
Researchers in Prof. Lei Xing's laboratory have developed a radioluminescent platform to combine molecular and X-ray imaging using standard X-ray equipment coupled with a photodetector.
Stanford researchers have developed a method that can tune the ratio between reversible (RE) and irreversible (IRE) electroporation through waveform adjustments.