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Results for "auto machine": 5 found

A Predictive Tool for Optimizing Treatment System Allocation in Hypofractionated Whole-Breast Radiotherapy

Authors: Zhenzhen Dai, Anthony J. Doemer, Ryan Hall, Kenneth Levin, Bing Luo, Benjamin Movsas, Karen C. Snyder, Kundan S Thind, Eleanor Walker

Affiliation: Henry Ford Health, HFHS

Abstract Preview: Purpose: To investigate the feasibility of a predictive tool for efficient allocation of hypofractionated whole-breast irradiation patients between Varian Truebeam and Ethos systems.
Methods: A ful...

Auto-Beam Hold Validation for Varian Sgrt Identify 3.0 on Truebeam Linear Accelerators

Authors: Hongyu Jiang, Wangyao Li, Dima Soultan, Fen Wang, Jun Xu

Affiliation: Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: To validate the Auto-Beam Hold functionality via the MMI connection between Varian SGRT system IDENTIFY 3.0 and treatment linacs.
Methods: A treatment plan was created in the Eclipse TPS u...

Clinical Implementation of Automated Contour Quality Assurance in Head and Neck Radiotherapy

Authors: Sam Armstrong, Jamison Louis Brooks, Nicole Johnson, Douglas John Moseley, Cassie Sonnicksen, Erik J. Tryggestad

Affiliation: Mayo Clinic

Abstract Preview: Purpose: To evaluate the feasibility of a shallow learning-based quality assurance (QA) tool designed to assist human reviewers in assessing organ-at-risk (OAR) contours for head and neck radiotherapy...

Commissioning of a 3D-CRT Planning Software for a Machine with Only Flattening-Filter Free Energy

Authors: Michalis Aristophanous, Steven Blum, Laura I. Cervino, Antonio L. Damato, Karen Episcopia, Chi Huang, Shih-Chi Lin, Michelle K. Savacool

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Varian Ethos (Varian Medical Systems, Palo Alto, CA) is a 6 MV flattening-filter-free (FFF) only machine, posing a challenge in creating homogeneous dose distributions when using manual 3D-CR...

Two-Stage Clustering and Auto Machine Learning to Predict Chemoradiation Response in Tumor Subregions on FDG PET for La-NSCLC

Authors: Stephen R. Bowen, Shijun Chen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Qianqian Tong, Jiajie Wang, Shouyi Wang, Faisal Yaseen

Affiliation: The University of Texas at Austin, Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington

Abstract Preview: Purpose: Tumor subregion clustering and prediction of region-specific response can augment assessments and adaptive treatment decisions. A modeling framework was constructed to predict chemoradiation ...