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Results for "guided intelligent": 6 found

A Dual Energy CT-Guided Intelligent Radiation Therapy Platform

Authors: Jiayi Chen, Manju Liu, Ning Wen, Haoran Zhang, Yibin Zhang

Affiliation: Department of Radiation Oncology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines...

Construction and Application Study of a Deep Learning-Based Iscout-Guided Precision Radiotherapy Positioning Error Prediction Model for Breast Cancer

Authors: Fangfen Dong, Jiaming Li, Xiaobo Li, Weipei Wang, Zhixin Wang, Bing Wu, Benhua Xu, Yong Yang, Yifa Zhao

Affiliation: Department of Radiation Oncology, Fujian Medical University Union Hospital/Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors/Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematologi, Zhangpu County Hospital, School of Medical Imaging, Fujian Medical University

Abstract Preview: Purpose: To explore the construction and clinical application value of a deep learning-based positioning error prediction model, providing a reference for optimizing iSCOUT system-guided precision rad...

Development of a Template-Based Planning Workflow for Offline Adaptive Head and Neck Cancer Using Ethos 2.0

Authors: Kaelyn Becker, Xenia Ray

Affiliation: University of California, San Diego, University of California San Diego

Abstract Preview: Purpose: Ethos 2.0 with HyperSight (Varian Medical Systems) imaging enables nearly fully automated offline adaptive radiotherapy including automated deformation of targets and recalculation on the Hou...

Integrating Knowledge-Based Planning with Ethos 2.0 for High-Quality Online Adaptive Lung SABR

Authors: Shahed Badiyan, Chien-Yi Liao, Mu-Han Lin, Dan Nguyen, Justin D. Visak, Hui Ju Wang, Brien Timothy Washington, Kenneth Westover, Yuanyuan Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose: Knowledge-based planning (KBP) plays a crucial role in improving treatment plans by leveraging previous clinical data to guide new cases. KBP is applied to the Ethos 2.0 Intelligent Optimizat...

Research on Glioma MRI Image Generation Based on Large Language Model and Diffusion Model

Authors: Xiangli Cui, Chi Han, Man Hu, Wanli Huo, Xunan Wang, Jianguang Zhang, Yingying Zhang

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, China Jiliang University,

Abstract Preview: Purpose:
Medical image generation has broad application prospects in deep learning, but the model training effect is often limited due to the lack of real image data. This study aims to explore the...

Scoring Functions for Reinforcement Learning in Accelerated Partial Breast Irradiation Treatment Planning

Authors: Rafe A. McBeth, Kuancheng Wang, Ledi Wang

Affiliation: Department of Radiation Oncology, University of Pennsylvania, Georgia Institute of Technology, University of Pennsylvania

Abstract Preview: Purpose:
The integration of AI in clinical workflows presents unprecedented opportunities to enhance treatment quality in radiation oncology, yet it also demands innovative approaches to address th...