Results 241 to 250 of about 51,447 (275)
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Patient-specific IMRT QA verification using machine learning and gamma radiomics
Physica Medica, 2021Gamma function is the standard methodology for comparing dose distributions. It is calculated in dedicated software, and its results verification is not performed. Thus we developed an automatic tool for patient-specific QA results verification through high accuracy machine learning (ML) models based on the radiomics characteristics extraction from ...
Jéssica Caroline, Lizar +4 more
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A statistical approach to IMRT patient‐specific QA
Medical Physics, 2012Purpose: The intensity modulated radiation therapy (IMRT) patient‐specific quality assurance (QA) (referred to as QA in this paper for simplicity) process is a time and resource intensive effort in every clinic. The use of a global QA tolerance criterion for all treatment sites may be too tight for some complex sites increasing false negatives and ...
Geethpriya, Palaniswaamy +4 more
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SU-GG-T-211: MapCHECK Patient Specific QA Cannot Suffice for MLC QA
Medical Physics, 2008Purpose: To demonstrate that MLC QA is an important aspect of an IMRT program, and cannot be substituted with patient specific QA using MapCHECK. Method and Materials: Two Elekta linacs in our clinic are currently being commissioned for IMRT from 3D conformal.
M Backer +4 more
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SBRT/SRS patient-specific QA using GAFchromicTM EBT3 and FilmQATM Pro software.
Journal of radiosurgery and SBRT, 2022The aim of this work is to verify the potential use of GAFchromicTM EBT3 and FILMQATM pro software for patient specific quality assurance (QA) for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT) treatment plans in clinical routine use.
Stella, Giuseppe +8 more
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Validation of clearcalc for efficient patient specific QA
Medical DosimetryUganda's only radiotherapy center is a very busy facility treating about 210 patients daily on three linear accelerators making it sometimes hard to have machine time for pretreatment QAs. This study was aimed at validating an independent calculation software, ClearCalc (ICS) for second checks of the treatment planning system (TPS) calculations.
Ignatius Komakech +4 more
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Monte Carlo based, patient‐specific RapidArc QA using Linac log files
Medical Physics, 2009PurposeA Monte Carlo (MC) based QA process to validate the dynamic beam delivery accuracy for Varian RapidArc™ (Varian Medical Systems, Palo Alto, CA) using Linac delivery log files (DynaLog) is presented. Using DynaLog file analysis and MC simulations, the goal of this article is to (a) confirm that adequate sampling is used in the RapidArc ...
Tony, Teke +5 more
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Multi-task autoencoder based classification-regression model for patient-specific VMAT QA
Physics in Medicine & Biology, 2020Abstract Patient-specific quality assurance (PSQA) of volumetric modulated arc therapy (VMAT) to assure accurate treatment delivery is resource-intensive and time-consuming. Recently, machine learning has been increasingly investigated in PSQA results prediction.
Le Wang +7 more
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SU-FF-T-245: Improvement of QA Pass-Rate in IMRT Patient Specific QA Using MapCHECK
Medical Physics, 2009Purpose: To demonstrate the improvement in IMRT patient specific quality assurance (QA) by considering a more accurate absolute dose calibration in MapCHECK, machine hardware characteristics and modification in beam modeling in treatment planning system (TPS). Method and Materials: MapCHECK, a 2D diode array system, was used in our routine IMRT patient
C Yang +6 more
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On the use of trajectory log files for machine & patient specific QA
Biomedical Physics & Engineering Express, 2020Abstract Purpose: Trajectory log files are increasingly being utilized clinically for machine and patient specific QA. The process of converting the DICOM-RT plan to a deliverable trajectory by the linac control software introduces some uncertainty that is inherently incorporated into measurement-based patient specific
Kai-Cheng Chuang +2 more
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On the use of biomathematical models in patient‐specific IMRT dose QA
Medical Physics, 2013Purpose:To investigate the use of biomathematical models such as tumor control probability (TCP) and normal tissue complication probability (NTCP) as new quality assurance (QA) metrics.Methods:Five different types of error (MLC transmission, MLC penumbra, MLC tongue and groove, machine output, and MLC position) were intentionally induced to 40 clinical
Heming, Zhen +2 more
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