Cargando…

Impact of CT scan parameters on deformable image registration accuracy using deformable thorax phantom

The purpose of this study was to evaluate the deformable image registration (DIR) accuracy using various CT scan parameters with deformable thorax phantom. Our developed deformable thorax phantom (Dephan, Chiyoda Technol Corp, Tokyo, Japan) was used. The phantom consists of a base phantom, an inner...

Descripción completa

Detalles Bibliográficos
Autores principales:	Ikeda, Ryutaro, Kadoya, Noriyuki, Nakajima, Yujiro, Ishii, Shin, Shibu, Takayuki, Jingu, Keiichi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2023
Materias:	Radiation Oncology Physics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10161117/ https://www.ncbi.nlm.nih.gov/pubmed/36840512 http://dx.doi.org/10.1002/acm2.13917

Ejemplares similares

Development of a physical geometric phantom for deformable image registration credentialing of radiotherapy centers for a clinical trial
por: Kadoya, Noriyuki, et al.
Publicado: (2021)

Dosimetric impact of deformable image registration using radiophotoluminescent glass dosimeters with a physical geometric phantom
por: Sakulsingharoj, Siwaporn, et al.
Publicado: (2023)

Validation of three deformable image registration algorithms for the thorax
por: Latifi, Kujtim, et al.
Publicado: (2013)

Quantifying the accuracy of deformable image registration for cone‐beam computed tomography with a physical phantom
por: Wu, Richard Y., et al.
Publicado: (2019)

Evaluation of accuracy of B-spline transformation-based deformable image registration with different parameter settings for thoracic images
por: Kanai, Takayuki, et al.
Publicado: (2014)

Validation of accuracy deformable image registration contour propagation using a benchmark virtual HN phantom dataset
por: Boyd, Robert, et al.
Publicado: (2021)

Evaluation of various deformable image registration algorithms for thoracic images
por: Kadoya, Noriyuki, et al.
Publicado: (2014)

Characterization of a new physical phantom for testing rigid and deformable image registration
por: Wu, Richard Y., et al.
Publicado: (2018)

Development of a deformable lung phantom for the evaluation of deformable registration
por: Chang, Jina, et al.
Publicado: (2010)

Accuracy of patient setup positioning using surface‐guided radiotherapy with deformable registration in cases of surface deformation
por: Kadman, Boriphat, et al.
Publicado: (2022)

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom
por: Wu, Richard Y., et al.
Publicado: (2019)

Using patient‐specific phantoms to evaluate deformable image registration algorithms for adaptive radiation therapy
por: Stanley, Nick, et al.
Publicado: (2013)

Factual survey of the clinical use of deformable image registration software for radiotherapy in Japan
por: Kadoya, Noriyuki, et al.
Publicado: (2019)

Evaluation of rectum and bladder dose accumulation from external beam radiotherapy and brachytherapy for cervical cancer using two different deformable image registration techniques
por: Kadoya, Noriyuki, et al.
Publicado: (2017)

Evaluation of the performance of deformable image registration between planning CT and CBCT images for the pelvic region: comparison between hybrid and intensity-based DIR
por: Takayama, Yoshiki, et al.
Publicado: (2017)

Accuracy quantification of a deformable image registration tool applied in a clinical setting
por: Hoffmann, Christoph, et al.
Publicado: (2014)

Deformable abdominal phantom for the validation of real‐time image guidance and deformable dose accumulation
por: Matrosic, Charles K., et al.
Publicado: (2019)

Variability in commercially available deformable image registration: A multi‐institution analysis using virtual head and neck phantoms
por: Kubli, Alex, et al.
Publicado: (2021)

Quantitative evaluation of the performance of different deformable image registration algorithms in helical, axial, and cone‐beam CT images using a mobile phantom
por: Ali, Imad, et al.
Publicado: (2018)

Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments
por: Li, Guang, et al.
Publicado: (2008)

Effect of Deformation Methods on the Accuracy of Deformable Image Registration From Kilovoltage CT to Tomotherapy Megavoltage CT
por: Nobnop, Wannapha, et al.
Publicado: (2019)

The evaluation of a hybrid biomechanical deformable registration method on a multistage physical phantom with reproducible deformation
por: Qin, An, et al.
Publicado: (2018)

On Thorax Resection for Empyema and the Resulting Deformities
por: Rutherfurd, Henry
Publicado: (1900)

Assessment of a commercially available automatic deformable registration system
por: Fallone, B. Gino, et al.
Publicado: (2010)

A measure to evaluate deformable registration fields in clinical settings
por: Schreibmann, Eduard, et al.
Publicado: (2012)

Investigation of dosimetric variations of liver radiotherapy using deformable registration of planning CT and cone‐beam CT
por: Huang, Pu, et al.
Publicado: (2016)

A framework for deformable image registration validation in radiotherapy clinical applications
por: Varadhan, Raj, et al.
Publicado: (2013)

Evaluation of the tool “Reg Refine” for user‐guided deformable image registration
por: Johnson, Perry B., et al.
Publicado: (2016)

Usefulness of hybrid deformable image registration algorithms in prostate radiation therapy
por: Motegi, Kana, et al.
Publicado: (2018)

A multiparametric method to assess the MIM deformable image registration algorithm
por: Calusi, Silvia, et al.
Publicado: (2019)

Objective Assessment of the Quality and Accuracy of Deformable Image Registration
por: Jurkovic, Ines-Ana, et al.
Publicado: (2020)

Dependence of ventilation image derived from 4D CT on deformable image registration and ventilation algorithms
por: Latifi, Kujtim, et al.
Publicado: (2013)

Benchmarking of five commercial deformable image registration algorithms for head and neck patients
por: Pukala, Jason, et al.
Publicado: (2016)

Deformable image registration and interobserver variation in contour propagation for radiation therapy planning
por: Riegel, Adam C., et al.
Publicado: (2016)

Validation of a deformable MRI to CT registration algorithm employing same day planning MRI for surrogate analysis
por: Padgett, Kyle R., et al.
Publicado: (2018)

Evaluation of patient DVH‐based QA metrics for prostate VMAT: correlation between accuracy of estimated 3D patient dose and magnitude of MLC misalignment
por: Kadoya, Noriyuki, et al.
Publicado: (2015)

Variations Between Dose-Ventilation and Dose-Perfusion Metrics in Radiation Therapy Planning for Lung Cancer
por: Nakajima, Yujiro, et al.
Publicado: (2020)

Deformable registration of chest CT images using a 3D convolutional neural network based on unsupervised learning
por: Zheng, Yongnan, et al.
Publicado: (2021)

Deformable registration using edge‐preserving scale space for adaptive image‐guided radiation therapy
por: Li, Dengwang, et al.
Publicado: (2011)

The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed
por: Xie, Xin, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_e58hlrdco0ubpd0c18uoh6scfv