Results 251 to 260 of about 18,422 (295)

Error detection and classification in patient‐specific IMRT QA with dual neural networks

Medical Physics, 2020
PurposeDespite being the standard metric in patient‐specific quality assurance (QA) for intensity‐modulated radiotherapy (IMRT), gamma analysis has two shortcomings: (a) it lacks sensitivity to small but clinically relevant errors (b) it does not provide efficient means to classify the error sources. The purpose of this work is to propose a dual neural
Nicholas J, Potter, Karl, Mund, Jacqueline M, Andreozzi, Jonathan G, Li, Chihray, Liu, Guanghua, Yan   +5 more
openaire   +2 more sources

Evaluation of a 2D detector array for patient-specific VMAT QA with different setups

Physics in Medicine and Biology, 2011
For pre-treatment plan verification of advanced treatment techniques such as intensity-modulated arc therapy, a fast and reliable dosimetric device is required. In this study, we investigated the suitability of MatriXX in different setups for verification of volumetric modulated arc therapy (VMAT) plans.
Boggula R, Birkner M, Lohr F, Steil V, Wenz F, Wertz H   +5 more
openaire   +4 more sources

SU-FF-T-245: Improvement of QA Pass-Rate in IMRT Patient Specific QA Using MapCHECK

Medical Physics, 2009
Purpose: 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, T Liu, H Zhou, J Cui, J Perks, R Stern, J Purdy   +6 more
openaire   +1 more source

Predicting the error magnitude in patient-specific QA during radiotherapy based on ResNet

Journal of X-Ray Science and Technology: Clinical Applications of Diagnosis and Therapeutics
BACKGROUND: The error magnitude is closely related to patient-specific dosimetry and plays an important role in evaluating the delivery of the radiotherapy plan in QA. No previous study has investigated the feasibility of deep learning to predict error magnitude.
Ying, Huang, Yifei, Pi, Kui, Ma, Xiaojuan, Miao, Sichao, Fu, Aihui, Feng, Yanhua, Duan, Qing, Kong, Weihai, Zhuo, Zhiyong, Xu   +9 more
openaire   +2 more sources

Film dosimetry with multichannel approach for proton therapy patient-specific QA

Physica Medica, 2016
Selected oral ...
Lorentini, S., MARRAZZO, LIVIA, PALLOTTA, STEFANIA, Schwarz, M.   +3 more
openaire   +1 more source

CHARACTERIZATION OF A PATIENT SPECIFIC PRE-TREATMENT QA SOFTWARE

Physica Medica, 2023
I. Cupparo, M. Casati, L. Enriquez, C. Arilli, S. Calusi, A. Compagnucci, L. Marrazzo, M. Zani, S. Pallotta, C. Talamonti   +9 more
openaire   +1 more source

Patient specific QA for RapidArc

Physica Medica, 2012
Sinéad Keogh, Elaine Tyner
openaire   +1 more source

Patient navigation across the cancer care continuum: An overview of systematic reviews and emerging literature

Ca-A Cancer Journal for Clinicians, 2023
Jolyn Johal, Matthew Tieu, Nicolas H Hart   +2 more
exaly  

PO-1374: Validation of SRS MapCheck for patient specific QA

Radiotherapy and Oncology, 2020
C. Anson Marcos, M. Roch González, D. Hernández González, P. Castro Tejero, A. Viñals Muñoz, R. Fayos-Solà Capilla, L. Pérez González   +6 more
openaire   +1 more source

A novel isodose surface-based method for patient specific QA analysis

Physica Medica, 2021
S. Diamantopoulos, K. Platoni, P. Karaiskos, V. Kouloulias, E. Efstathopoulos   +4 more
openaire   +1 more source