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Results for "uncertainty machine": 10 found

A Novel Non-Measured and DVH-Based IMRT QA Framework with Machine Learning for Instant Classification of Susceptible Lung SBRT VMAT Plans

Authors: Chuan He, Anh H. Le, Iris Z. Wang

Affiliation: Roswell Park Comprehensive Cancer Center, Cedars-Sinai

Abstract Preview: Purpose: To develop a non-measured and DVH-based (NMDB) IMRT QA framework integrating machine learning (ML) to classify lung SBRT VMAT plans prone to delivery errors
Methods: 560 Eclipse AcurosXB l...

Enhancing Robustness in Proton Therapy through Online Adaptive Workflow: An in-Silico Study

Authors: Robbie Beckert, Weiren Liu, Thomas R. Mazur, Allen Mo, Stephanie Perkins, Hailei Zhang, Tianyu Zhao

Affiliation: Washington University in St. Louis School of Medicine, University of South Florida, WashU Medicine

Abstract Preview: Purpose: Online adaptation may mitigate uncertainties in proton therapy arising from interfractional anatomical changes. While robust optimization accounts for setup and range uncertainties during pla...

Impact of Jaw Reproducibility and Source Occlusion on Small Field Dosimetry

Authors: Mylinh Dang, Indra J. Das, George X. Ding, Ahtesham Ullah U Khan, Andrew J. White

Affiliation: Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern Medicine, Vanderbilt University Medical Center

Abstract Preview: Purpose: The large variability in field output factor (FOF) observed among various studies is speculated to be due to uncertainty in jaw reproducibility that is linked directly with source occlusion. ...

Inter-Patient Adaptive Radiotherapy (IPART): A CT Simulation and Planning Free Approach Enabling Immediate Treatment Access for Patients.

Authors: Bin Cai, Andrew R. Godley, Brian A. Hrycushko, Heejung Kim, Mu-han Lin, David D.M. Parsons, Justin D. Visak, Da Wang, Tingliang Zhuang

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

Abstract Preview: Purpose: The standard radiation therapy workflow requires CT-simulation and planning, whether for initial treatments or re-planning due to significant anatomical changes. IPART instead uses one patien...

Mid-Range Planning for Efficient and Robust Proton Arc Therapy

Authors: Mingli Chen, Xuejun Gu, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, Kangning Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: Delivery efficiency and robustness are critical in spot-scanning proton arc therapy (SPAT), yet the conventional use of redundant energy layers (ELs) prolongs switching times and reduces effi...

Mitigating Data-Driven Uncertainty in Machine Learning-Based Radiotherapy Outcome Prediction

Authors: Ali Ajdari, Alice Bondi, Thomas R. Bortfeld, Gregory Buti, Xinru Chen, Zhongxing Liao, Antony John Lomax, Ting Xu

Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Paul Scherrer Institut, ETH Zurich

Abstract Preview: Title: Addressing Imaging and Biomarker-driven Uncertainty in Machine Learning-based Radiotherapy Outcome Prediction
Alice Bondi, Gregory Buti, Antony Lomax, Thomas Bortfeld, Xinru Chen, Ting Xu, Z...

Multi-Vendor Linac Isocenter Evaluation: Implications for SRS in Radiotherapy

Authors: Blessing Chinelo Akah, Brad Barhorst, Daniel W. Neck, David J. Perrin, Chad Robertson, Sotirios Stathakis

Affiliation: Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: To evaluate the performance and radiation isocenter of Elekta and Varian linear accelerator using Aktina Isopoint.
Methods: The Aktina Isopoint was used to measure the physical and radiati...

Optimizing Fractionation Schedules for De-Escalation Radiotherapy in Head and Neck Cancers Using Deep Reinforcement Learning

Authors: Zhongjie Lu

Affiliation: Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine

Abstract Preview: Purpose: Patients with locally-advanced head and neck squamous cell carcinomas(HNSCCs), particularly those related to human papillomavirus(HPV), often achieve good locoregional control(LRC), yet they ...

Predicting Brain V60% in Linac-Based Single-Isocenter-Multiple-Targets (SIMT) Stereotactic Radiosurgery Using Machine Learning

Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...

Respiratory Monitoring in Human Subjects Using a Low-Cost Optical Imaging System Prototype

Authors: Marian Axente, Mandeep Kaur

Affiliation: Emory University

Abstract Preview: Purpose: To validate a low-cost optical imaging system for respiratory monitoring by comparing its accuracy and feasibility against the clinical gold standard in human subjects.
Methods: Following ...