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Results for "contour platform": 11 found

A Beagle Dog Mesh-Type Phantom for Application to Nuclear Medicine and Internal Dosimetry

Authors: Wesley E. Bolch, Natalia Estefania Carrasco-Rojas, Chansoo Choi, Robert Joseph Dawson, Aitor Gallastegui Menoyo, Rowan James Milner, Bangho Shin, Maria M. Von Chamier

Affiliation: University of Florida

Abstract Preview: Purpose: To develop a tetrahedralizable mesh-type phantom of a male beagle dog to later perform Monte Carlo radiation transport simulations and calculate organ doses using monoenergetic photons, elect...

Analysis of Structure Errors in Region of Interest Contouring for Radiotherapy Planning: A Study Using the RT-Contour QA Platform

Authors: Sijuan Huang, Zi LIU, Jing MA, Xin Yang

Affiliation: Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, Guangdong, 510060, China

Abstract Preview: Purpose: To reduce the pressure of manual review of abnormal situations in manually/automatically delineated regions of interest (ROI), improve its accuracy and basis.
Methods: 220 radiotherapy pat...

Automated Decision Workflow Using Fast Monte Carlo Dose Calculations for Daily Adaptive Proton Therapy

Authors: Ergun E. Ahunbay, Abdul Parchur, Eric S. Paulson, Ilaria Rinaldi, Angelo Schiavi, Li Zhao

Affiliation: Sapienza University of Rome, Department of Radiation Oncology (Maastro), GROW School for Oncology, Maastricht University Medical Centre+, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Online adaptive replanning is often necessary in Intensity Modulated Proton Therapy (IMPT) due to the sensitivity of proton dose distributions to daily anatomical changes. A rapid, automated ...

Automated Multimodal Image Registration for Prostate Bed Radiation Treatment

Authors: Quan Chen, Xue Feng, Chunhui Han, Gaofeng Huang, Trevor Ketcherside, Yi Lao, Yun Rose Li, An Liu, Bo Liu, Kun Qing, William T. Watkins

Affiliation: Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, City of Hope National Medical Center, Mayo Clinic Arizona, Carina Medical LLC

Abstract Preview: Purpose: New treatment platforms such as Ethos (Varian Medical Systems) allow the introduction of multi-modal imaging into adaptive radiotherapy workflow to facilitate an up-to-date view of patients’ ...

Deep Learning-Based Ventricular Auto-Segmentation for Dosimetric Analysis in Intraventricular Tumor SRS

Authors: John Byun, Juan J Cardona, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Yusuke Hori, Hao Jiang, Fred Lam, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang

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

Abstract Preview: Purpose:
Intraventricular tumors pose significant challenges in neurosurgery due to their complex location. Therefore, brain SRS could be a better treatment option. At our institution, some patient...

Development and Validation of a Deep Learning-Based Auto-Segmentation Module for Vestibular Schwannoma

Authors: John Byun, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Xianghua Ye, Kangning Zhang

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

Abstract Preview: Purpose: Accurate and automated delineation of vestibular schwannoma (VS) volume is crucial for disease management, as both treatment approaches (stereotactic radiosurgery and invasive surgery) and mo...

Dosimetric Impact of Auto-Segmentation with Replanning: An Analysis of a Prospective Clinical Trial

Authors: Kathryn J. Dess, Martha M. Matuszak, Dan Polan

Affiliation: University of Michigan

Abstract Preview: Purpose: A recent survey demonstrated 18 of 20 top academic institutions have implemented auto-segmentation. Studies to date have focused on geometric contour changes and dosimetric differences using ...

Evaluating Commercial Auto-Segmentation Software: Is Performance on Pediatric Organs-at-Risk Accurate?

Authors: Gregory T. Armstrong, James E. Bates, Lei Dong, Ralph Ermoian, Jie Fu, Christine Hill-Kayser, Rebecca M. Howell, Sharareh Koufigar, John T. Lucas, Thomas E. Merchant, Tucker J. Netherton, Sogand Sadeghi

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, St. Jude Children's Research Hospital, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, St. Jude Children’s Research Hospital, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, University of Washington/ Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study evaluates the adaptability and limitations of commercially available (MIM, RayStation) tools trained on predominately adult datasets (ages 20–60+ years) for delineating organs at r...

Expanding the Reach: Integrating AI-Generated Auto Contours Via Ray Station’s Deep Learning Segmentation into Diverse Treatment Planning Systems

Authors: Raghavendra Raghavendra, Kanaparthy Raja Muralidhar, Venkataramanan Ramachandran, Srinivas Srinivas

Affiliation: Karkinos Healthcare

Abstract Preview: Purpose: This study explores the Integrating AI-Generated Auto Contours via Ray Station’s Deep Learning Segmentation into Diverse Treatment Planning Systems.
Methods: The research encompassed a gro...

FMEA for Direct to Unit Adaptive Radiotherapy

Authors: Haleem Azmy, Robbie Beckert, Farnoush Forghani, Dean Hobbis, Dan Hong, Hyun Kim, Eric Laugeman, Silpa Raju-Salicki, Domenic Sievert

Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine in St. Louis, Washington University School of Medicine, Wash U Medicine, Washington University in St. Louis

Abstract Preview: Purpose: A novel radiation therapy (RT) workflow has recently emerged with the advent of online adaptive RT systems, direct-to-unit (DTU). DTU utilizes online adaptive platforms (MR and CT based) to o...

Investigation of Triggered Imaging and Auto Beam Hold Using a Dynamic Thorax Phantom for Intra-Fraction Motion Management

Authors: Liu Hong, Zhong Su

Affiliation: University of Arkansas for Medical Sciences, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)

Abstract Preview: Purpose: During treatment delivery on TrueBeam platform 2.7, Triggered Imaging (TI) enables kV images acquisition at regular intervals and Auto Beam Hold (ABH) provides beam pausing if the target is m...