Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy

ilustraciones, graficas

Autores:: Agudelo Angarita, Daniel José

Tipo de recurso:

Fecha de publicación:: 2022

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: eng

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repository_id_str
dc.title.eng.fl_str_mv	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
dc.title.translated.spa.fl_str_mv	Validación del registro deformable de imagen basado en contornos para acumulación de dosis en radioterapia de haz externo
title	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
spellingShingle	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy 530 - Física::539 - Física moderna Acumulación de dosis Registro de imagen Registro deformable de imagen Algoritmo ANACONDA de Raystation Cáncer de pulmón de célula no pequeña Radioterapia estereotáctica de cuerpo Estimación de incertidumbre Dose accumulation Image registration Deformable image registration ANACONDA Raystation algorithm Non small cell lung cancer Stereotactic body radiation therapy Uncertainty estimation
title_short	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
title_full	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
title_fullStr	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
title_full_unstemmed	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
title_sort	Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy
dc.creator.fl_str_mv	Agudelo Angarita, Daniel José
dc.contributor.advisor.none.fl_str_mv	Lechner, Wolfgang Plazas, Maria Cristina
dc.contributor.author.none.fl_str_mv	Agudelo Angarita, Daniel José
dc.contributor.researchgroup.spa.fl_str_mv	Grupo Fisica Medica Unalb
dc.subject.ddc.spa.fl_str_mv	530 - Física::539 - Física moderna
topic	530 - Física::539 - Física moderna Acumulación de dosis Registro de imagen Registro deformable de imagen Algoritmo ANACONDA de Raystation Cáncer de pulmón de célula no pequeña Radioterapia estereotáctica de cuerpo Estimación de incertidumbre Dose accumulation Image registration Deformable image registration ANACONDA Raystation algorithm Non small cell lung cancer Stereotactic body radiation therapy Uncertainty estimation
dc.subject.proposal.spa.fl_str_mv	Acumulación de dosis Registro de imagen Registro deformable de imagen Algoritmo ANACONDA de Raystation Cáncer de pulmón de célula no pequeña Radioterapia estereotáctica de cuerpo Estimación de incertidumbre
dc.subject.proposal.eng.fl_str_mv	Dose accumulation Image registration Deformable image registration ANACONDA Raystation algorithm Non small cell lung cancer Stereotactic body radiation therapy Uncertainty estimation
description	ilustraciones, graficas
publishDate	2022
dc.date.accessioned.none.fl_str_mv	2022-11-03T16:41:24Z
dc.date.available.none.fl_str_mv	2022-11-03T16:41:24Z
dc.date.issued.none.fl_str_mv	2022
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
dc.identifier.uri.none.fl_str_mv	https://repositorio.unal.edu.co/handle/unal/82622
dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/82622 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	eng
language	eng
dc.relation.indexed.spa.fl_str_mv	RedCol LaReferencia
dc.relation.references.spa.fl_str_mv	Taoran Li, Xiaofeng Zhu, Danthai Thongphiew, W. Robert Lee, Zeljko Vujaskovic, Qiuwen Wu, Fang-Fang Yin, and Q. Jackie Wu. On-line adaptive radiation therapy: Feasibility and clinical study. Journal of Oncology, 2010:407236, Nov 2010. Kristy K. Brock, Sasa Mutic, Todd R. McNutt, Hua Li, and Marc L. Kessler. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the aapm radiation therapy committee task group no. 132. Medical Physics, 44(7):e43–e76, 2017. Ola Weistrand and Stina Svensson. The anaconda algorithm for deformable image registration in radiotherapy. Medical Physics, 42(1):40–53, 2015. Charles K. Matrosic, Jennifer Hull, Benjamin Palmer, Wesley Culberson, and Bryan Bednarz. Deformable abdominal phantom for the validation of real-time image guidance and deformable dose accumulation. Journal of Applied Clinical Medical Physics, 20(8):122–133, 2019. Ervin B. Podgoršak. Interactions of Photons with Matter, pages 277–375. Springer Berlin Heidelberg, Berlin, Heidelberg, 2010. Indrin J. Chetty and Mihaela Rosu-Bubulac. Deformable registration for dose accumulation. Seminars in Radiation Oncology, 29(3):198–208, 2019. Adaptive Radiotherapy and Automation. Thomas S. Huang. Computer vision: Evolution and promise. 1996. L.G Brown. A survey of image registration techniques. ACM computer surveys, 24:325–376, 1992. Bastien Rigaud, Antoine Simon, Joël Castelli, Caroline Lafond, Oscar Acosta, Pascal Haigron, Guillaume Cazoulat, and Renaud de Crevoisier. Deformable image registration for radiation therapy: principle, methods, applications and evaluation. Acta Oncologica, 58(9):1225–1237, 2019. PMID: 31155990. Kristy K. Brock. Adaptive radiotherapy: Moving into the future. Seminars in Radiation Oncology, 29(3):181–184, 2019. Adaptive Radiotherapy and Automation. Lauren Henke, Rojano Kashani, Deshan Yang, Tianyu Zhao, Olga Green, Lindsey Olsen, Vivian Rodriguez, H. Omar Wooten, H. Harold Li, Yanle Hu, Jeffrey Bradley, Clifford Robinson, Parag Parikh, Jeff Michalski, Sasa Mutic, and Jeffrey R. Olsen. Simulated online adaptive magnetic resonance–guided stereotactic body radiation therapy for the treatment of oligometastatic disease of the abdomen and central thorax: Characterization of potential advantages. International Journal of Radiation Oncology, Biology, Physics, 96(5):1078–1086, Dec 2016. Carri K. Glide-Hurst, Percy Lee, Adam D. Yock, Jeffrey R. Olsen, Minsong Cao, Farzan Siddiqui, William Parker, Anthony Doemer, Yi Rong, Amar U. Kishan, Stanley H. Benedict, X. Allen Li, Beth A. Erickson, Jason W. Sohn, Ying Xiao, and Evan Wuthrick. Adaptive radiation therapy (art) strategies and technical considerations: A state of the art review from nrg oncology. International Journal of Radiation OncologyBiologyPhysics, 109(4):1054–1075, 2021. Jolien Heukelom and Clifton David Fuller. Head and neck cancer adaptive radiation therapy (art): Conceptual considerations for the informed clinician. Seminars in Radiation Oncology, 29(3):258–273, 2019. Adaptive Radiotherapy and Automation. Aristeidis Sotiras, Christos Davatzikos, and Nikos Paragios. Deformable medical image registration: A survey. IEEE Transactions on Medical Imaging, 32(7):1153–1190, 2013. J. Maintz and Viergever. An overview of medical image registration methods. 1998. Jef Vandemeulebroucke, David Sarrut, Patrick Clarysse, et al. The popi-model, a pointvalidated pixel-based breathing thorax model. In XVth international conference on the use of computers in radiation therapy (ICCR), volume 2, pages 195–199. Citeseer, 2007. Jason Pukala, Perry B. Johnson, Amish P. Shah, Katja M. Langen, Frank J. Bova, Robert J. Staton, Rafael R. Manon, Patrick Kelly, and Sanford L. Meeks. Benchmarking of five commercial deformable image registration algorithms for head and neck patients. Journal of Applied Clinical Medical Physics, 17(3):25–40, 2016. Daniella Fabri, Valentina Zambrano, Amon Bhatia, Hugo Furtado, Helmar Bergmann, Markus Stock, Christoph Bloch, Carola Lütgendorf-Caucig, Supriyanto Pawiro, Dietmar Georg, Wolfgang Birkfellner, and Michael Figl. A quantitative comparison of the performance of three deformable registration algorithms in radiotherapy. Zeitschrift fur medizinische Physik, 23(4):279–290, Dec 2013. 23969092[pmid]. T. Sørensen. A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on danish commonss. K. Dan. Videnskabernes Selsks, 5(4):1–34, 1948. Jayaram K. Udupa, Vicki R. LeBlanc, Ying Zhuge, Celina Imielinska, Hilary Schmidt, Leanne M. Currie, Bruce E. Hirsch, and James Woodburn. A framework for evaluating image segmentation algorithms. Computerized Medical Imaging and Graphics, 30(2):75–87, 2006. Faiz M Khan and John P Gibbons. Khan’s the physics of radiation therapy. Lippincott Williams & Wilkins, 2014. E. M. Yoshimura. Fundamentals of Dosimetry Chapter 3. IAEA, International Atomic Energy Agency (IAEA), 2014. RADIATION PROTECTION AND DOSIMETRY. Definitions of basic quantities and terms. Journal of the ICRU, 14(1):9–13, 2014. PMID: 27789594. Juan Diego Azcona, Carlos Huesa-Berral, Marta Moreno-Jiménez, Benigno Barbés, José Javier Aristu, and Javier Burguete. A novel concept to include uncertainties in the evaluation of stereotactic body radiation therapy after 4d dose accumulation using deformable image registration. Medical Physics, 46(10):4346–4355, 2019. Yulun He, Guillaume Cazoulat, Carol Wu, Christine Peterson, Molly McCulloch, Brian Anderson, Julianne Pollard-Larkin, Peter Balter, Zhongxing Liao, Radhe Mohan, and Kristy Brock. Geometric and dosimetric accuracy of deformable image registration between average-intensity images for 4dct-based adaptive radiotherapy for non-small cell lung cancer. Journal of Applied Clinical Medical Physics, 22(8):156–167, 2021. Catarina Veiga, Ana Mónica Lourenço, Syed Mouinuddin, Marcel van Herk, Marc Modat, Sébastien Ourselin, Gary Royle, and Jamie R. McClelland. Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm. Medical Physics, 42(2):760–769, 2015. Nahla K. Saleh-Sayah, Elisabeth Weiss, Francisco J. Salguero, and Jeffrey V. Siebers. A distance to dose difference tool for estimating the required spatial accuracy of a displacement vector field. Medical Physics, 38(5):2318–2323, 2011. Navid Samavati, Michael Velec, and Kristy K. Brock. Effect of deformable registration uncertainty on lung sbrt dose accumulation. Medical Physics, 43(1):233–240, 2016. Francisco J. Salguero, Nahla K. Saleh-Sayah, Chenyu Yan, and Jeffrey V. Siebers. Estimation of three-dimensional intrinsic dosimetric uncertainties resulting from using deformable image registration for dose mapping. Medical Physics, 38(1):343–353, 2011. Rafael García-Mollá, Noelia de Marco-Blancas, Jorge Bonaque, Laura Vidueira, Juan López-Tarjuelo, and José Perez-Calatayud. Validation of a deformable image registration produced by a commercial treatment planning system in head and neck. Physica Medica: European Journal of Medical Physics, 31, May 2015. Neil Kirby, Josephine Chen, Hojin Kim, Olivier Morin, Ke Nie, and Jean Pouliot. An automated deformable image registration evaluation of confidence tool. Physics in Medicine and Biology, 61(8):N203–N214, mar 2016. Lena Nenoff, Cássia O. Ribeiro, Michael Matter, Luana Hafner, Mirjana Josipovic, Johannes A. Langendijk, Gitte F. Persson, Marc Walser, Damien Charles Weber, Antony John Lomax, Antje-Christin Knopf, Francesca Albertini, and Ye Zhang. Deformable image registration uncertainty for inter-fractional dose accumulation of lung cancer proton therapy. Radiotherapy and Oncology, 147:178–185, 2020. Florian Amstutz, Lena Nenoff, Francesca Albertini, Cássia O Ribeiro, Antje C Knopf, Jan Unkelbach, Damien C Weber, Antony J Lomax, and Ye Zhang. An approach for estimating dosimetric uncertainties in deformable dose accumulation in pencil beam scanning proton therapy for lung cancer. Physics in Medicine & Biology, 66(10):105007, may 2021. Chiara Paganelli, Giorgia Meschini, Silvia Molinelli, Marco Riboldi, and Guido Baroni. Patient-specific validation of deformable image registration in radiation therapy: Overview and caveats. Medical Physics, 45(10):e908–e922, 2018. Mirek Fatyga, Nesrin Dogan, Elizabeth Weiss, William C. Sleeman, Baoshe Zhang, William J. Lehman, Jeffrey F. Williamson, Krishni Wijesooriya, and Gary E. Christensen. A voxel-by-voxel comparison of deformable vector fields obtained by three deformable image registration algorithms applied to 4dct lung studies. Frontiers in Oncology, 5, 2015. Christopher L. Guy, Elisabeth Weiss, Shaomin Che, Nuzhat Jan, Sherry Zhao, and Mihaela Rosu-Bubulac. Evaluation of image registration accuracy for tumor and organs at risk in the thorax for compliance with tg 132 recommendations. Advances in Radiation Oncology, 4(1):177–185, 2019.
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ciencias - Maestría en Física Médica
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Lechner, Wolfgangcd95238e36f3f792a776d8864e7790c7Plazas, Maria Cristinaeb00c560439ba84760a062d7ca6bc2b0Agudelo Angarita, Daniel José4ddddf2c0ad66608e91e66892d5b2750Grupo Fisica Medica Unalb2022-11-03T16:41:24Z2022-11-03T16:41:24Z2022https://repositorio.unal.edu.co/handle/unal/82622Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, graficasThe purpose of this project is to study and characterize a framework to evaluate deformable image registration (DIR) in the context of dose accumulation to account for intrafractional anatomical changes in external beam radiotherapy. The selected cohort of patients included 10 non small cell lung cancer (NSCLC) studies, each one composed of 10 computer tomography (CT) images taken over the breathing cycle. The full exhalation image was selected as reference for every patient and DIR was performed with the ANACONDA algorithm, included in Raystation treatment planning system (TPS). Four set ups of the algorithm were used for each registration and the resultant deformation vector field (DVF) was evaluated using manually drawn CTV contours as gold standards. Available metrics in the TPS, consisted on Dice similarity coefficient (DSC), mean distance to agreement (MDA), Hausdorff distance (HD) and Pearson correlation coefficient defined over the body and the CTVs region of interest (ROI). The results of this metrics over the breathing cycle were analyzed and compared with other available studies of the literature. Each patient had 3D-CRT and VMAT plans created on Raystation TPS, according to the stereotactic body radiation therapy (SBRT) protocol. To account for uncertainty propagation to the accumulated doses, variability over the four setups were used as a surrogate. Standard deviation distributions (STD) were calculated and evaluated using common dose volume histogram (DVH) parameters such as D95, D2, mean and maximun dose, calculated on target and organ at risk structures. This data was correlated with the previous geometrical metrics. Spearman correlations with statistical significance (p < 0,001) gave moderate to strong correlations, the strongest being r = 0,91 and −0,91 between D2 on ipsilateral lung and initial MDA and average STD dose on PTV and Pearson coefficient, respectively. Moderate correlations included r = 0,50 between D95 on PTV and HD among others. The analysis showed the framework as a way to clinically evaluate the accumulated dose and the usefulness of the dose standard deviation as a metric to achieve this goal.El propósito de este proyecto es el de estudiar y caracterizar un protocolo para evaluación de registro deformable de imagen (DIR) en el contexto de acumulación de dosis para cuantificar cambios anatómicos intrafraccionarios en pacientes de radioterapia de haz externo. La cohorte de pacientes incluyó 10 estudios de cáncer de pulmón de célula no-pequeña (NSCLC), cada uno compuesto por 10 imágenes de tomografía computarizada (CT) tomadas sobre el ciclo de respiración. La imagen de exhalación plena fue seleccionada como referencia para cada paciente y el DIR fue realizado con el algoritmo ANACONDA, incluido en el sistema de planeación de tratamiento (TPS) Raystation. Cuatro configuraciones fueron usadas para cada registro y el campo vectorial de deformación resultante (DVF) fue evaluado utilizando los contornos dibujados manualmente como estándar de referencia. Métricas disponibles en el TPS consistieron en el coeficiente de similaridad de DICE (DSC), la distancia promedio de concordancia (MDA), la distancia de Hausdorff (HD) y el coeficiente de correlación de Pearson definido sobre los ROI de cuerpo y de CTV. Los resultados de estas métricas sobre el ciclo de respiración fueron analizados y comparados con resultados de la literatura. Cada paciente tenía planes de 3D-CRT y VMAT creados en Raystation, de acuerdo al protocolo de radioterapia estereotáctica de cuerpo (SBRT). Para cuantificar la propagación de la incertidumbre sobre las dosis acumuladas, la variabilidad sobre las cuatro configuraciones fue usada como subrogado. Distribuciones de desviación estándar fueron calculadas y evaluadas usando parámetros comunes del histograma dosis volumen (DVH) como D95, D2, dosis promedio y máxima, calculadas en estructuras de objetivo y órganos a riesgo. Correlaciones de Spearman con significancia estadística (p<0,001) dieron correlaciones moderadas y fuertes, la mayor siendo r = 0, 91 y −0, 91 entre D2 en el pulmón ipsilateral y MDA inicial y la dosis STD en PTV y el coeficiente de Pearson, respectivamente. Correlaciones moderadas incluyeron r = 0, 50 entre D95 en PTV y HD entre otros. El análisis mostró el método como una forma clínica de evaluar la dosis acumulada y la utilidad de la desviación estándar de la dosis como métrica para lograr este propósito. (Texto tomado de la fuente)MaestríaMagíster en Física Médicaxiv, 50 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Física MédicaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá530 - Física::539 - Física modernaAcumulación de dosisRegistro de imagenRegistro deformable de imagenAlgoritmo ANACONDA de RaystationCáncer de pulmón de célula no pequeñaRadioterapia estereotáctica de cuerpoEstimación de incertidumbreDose accumulationImage registrationDeformable image registrationANACONDA Raystation algorithmNon small cell lung cancerStereotactic body radiation therapyUncertainty estimationValidation of deformable image registration based on contours for dose accumulation in external beam radiotherapyValidación del registro deformable de imagen basado en contornos para acumulación de dosis en radioterapia de haz externoTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMRedColLaReferenciaTaoran Li, Xiaofeng Zhu, Danthai Thongphiew, W. Robert Lee, Zeljko Vujaskovic, Qiuwen Wu, Fang-Fang Yin, and Q. Jackie Wu. On-line adaptive radiation therapy: Feasibility and clinical study. Journal of Oncology, 2010:407236, Nov 2010.Kristy K. Brock, Sasa Mutic, Todd R. McNutt, Hua Li, and Marc L. Kessler. Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the aapm radiation therapy committee task group no. 132. Medical Physics, 44(7):e43–e76, 2017.Ola Weistrand and Stina Svensson. The anaconda algorithm for deformable image registration in radiotherapy. Medical Physics, 42(1):40–53, 2015.Charles K. Matrosic, Jennifer Hull, Benjamin Palmer, Wesley Culberson, and Bryan Bednarz. Deformable abdominal phantom for the validation of real-time image guidance and deformable dose accumulation. Journal of Applied Clinical Medical Physics, 20(8):122–133, 2019.Ervin B. Podgoršak. Interactions of Photons with Matter, pages 277–375. Springer Berlin Heidelberg, Berlin, Heidelberg, 2010.Indrin J. Chetty and Mihaela Rosu-Bubulac. Deformable registration for dose accumulation. Seminars in Radiation Oncology, 29(3):198–208, 2019. Adaptive Radiotherapy and Automation.Thomas S. Huang. Computer vision: Evolution and promise. 1996.L.G Brown. A survey of image registration techniques. ACM computer surveys, 24:325–376, 1992.Bastien Rigaud, Antoine Simon, Joël Castelli, Caroline Lafond, Oscar Acosta, Pascal Haigron, Guillaume Cazoulat, and Renaud de Crevoisier. Deformable image registration for radiation therapy: principle, methods, applications and evaluation. Acta Oncologica, 58(9):1225–1237, 2019. PMID: 31155990.Kristy K. Brock. Adaptive radiotherapy: Moving into the future. Seminars in Radiation Oncology, 29(3):181–184, 2019. Adaptive Radiotherapy and Automation.Lauren Henke, Rojano Kashani, Deshan Yang, Tianyu Zhao, Olga Green, Lindsey Olsen, Vivian Rodriguez, H. Omar Wooten, H. Harold Li, Yanle Hu, Jeffrey Bradley, Clifford Robinson, Parag Parikh, Jeff Michalski, Sasa Mutic, and Jeffrey R. Olsen. Simulated online adaptive magnetic resonance–guided stereotactic body radiation therapy for the treatment of oligometastatic disease of the abdomen and central thorax: Characterization of potential advantages. International Journal of Radiation Oncology, Biology, Physics, 96(5):1078–1086, Dec 2016.Carri K. Glide-Hurst, Percy Lee, Adam D. Yock, Jeffrey R. Olsen, Minsong Cao, Farzan Siddiqui, William Parker, Anthony Doemer, Yi Rong, Amar U. Kishan, Stanley H. Benedict, X. Allen Li, Beth A. Erickson, Jason W. Sohn, Ying Xiao, and Evan Wuthrick. Adaptive radiation therapy (art) strategies and technical considerations: A state of the art review from nrg oncology. International Journal of Radiation OncologyBiologyPhysics, 109(4):1054–1075, 2021.Jolien Heukelom and Clifton David Fuller. Head and neck cancer adaptive radiation therapy (art): Conceptual considerations for the informed clinician. Seminars in Radiation Oncology, 29(3):258–273, 2019. Adaptive Radiotherapy and Automation.Aristeidis Sotiras, Christos Davatzikos, and Nikos Paragios. Deformable medical image registration: A survey. IEEE Transactions on Medical Imaging, 32(7):1153–1190, 2013.J. Maintz and Viergever. An overview of medical image registration methods. 1998.Jef Vandemeulebroucke, David Sarrut, Patrick Clarysse, et al. The popi-model, a pointvalidated pixel-based breathing thorax model. In XVth international conference on the use of computers in radiation therapy (ICCR), volume 2, pages 195–199. Citeseer, 2007.Jason Pukala, Perry B. Johnson, Amish P. Shah, Katja M. Langen, Frank J. Bova, Robert J. Staton, Rafael R. Manon, Patrick Kelly, and Sanford L. Meeks. Benchmarking of five commercial deformable image registration algorithms for head and neck patients. Journal of Applied Clinical Medical Physics, 17(3):25–40, 2016.Daniella Fabri, Valentina Zambrano, Amon Bhatia, Hugo Furtado, Helmar Bergmann, Markus Stock, Christoph Bloch, Carola Lütgendorf-Caucig, Supriyanto Pawiro, Dietmar Georg, Wolfgang Birkfellner, and Michael Figl. A quantitative comparison of the performance of three deformable registration algorithms in radiotherapy. Zeitschrift fur medizinische Physik, 23(4):279–290, Dec 2013. 23969092[pmid].T. Sørensen. A method of establishing groups of equal amplitude in plant sociology based on similarity of species and its application to analyses of the vegetation on danish commonss. K. Dan. Videnskabernes Selsks, 5(4):1–34, 1948.Jayaram K. Udupa, Vicki R. LeBlanc, Ying Zhuge, Celina Imielinska, Hilary Schmidt, Leanne M. Currie, Bruce E. Hirsch, and James Woodburn. A framework for evaluating image segmentation algorithms. Computerized Medical Imaging and Graphics, 30(2):75–87, 2006.Faiz M Khan and John P Gibbons. Khan’s the physics of radiation therapy. Lippincott Williams & Wilkins, 2014.E. M. Yoshimura. Fundamentals of Dosimetry Chapter 3. IAEA, International Atomic Energy Agency (IAEA), 2014. RADIATION PROTECTION AND DOSIMETRY.Definitions of basic quantities and terms. Journal of the ICRU, 14(1):9–13, 2014. PMID: 27789594.Juan Diego Azcona, Carlos Huesa-Berral, Marta Moreno-Jiménez, Benigno Barbés, José Javier Aristu, and Javier Burguete. A novel concept to include uncertainties in the evaluation of stereotactic body radiation therapy after 4d dose accumulation using deformable image registration. Medical Physics, 46(10):4346–4355, 2019.Yulun He, Guillaume Cazoulat, Carol Wu, Christine Peterson, Molly McCulloch, Brian Anderson, Julianne Pollard-Larkin, Peter Balter, Zhongxing Liao, Radhe Mohan, and Kristy Brock. Geometric and dosimetric accuracy of deformable image registration between average-intensity images for 4dct-based adaptive radiotherapy for non-small cell lung cancer. Journal of Applied Clinical Medical Physics, 22(8):156–167, 2021.Catarina Veiga, Ana Mónica Lourenço, Syed Mouinuddin, Marcel van Herk, Marc Modat, Sébastien Ourselin, Gary Royle, and Jamie R. McClelland. Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm. Medical Physics, 42(2):760–769, 2015.Nahla K. Saleh-Sayah, Elisabeth Weiss, Francisco J. Salguero, and Jeffrey V. Siebers. A distance to dose difference tool for estimating the required spatial accuracy of a displacement vector field. Medical Physics, 38(5):2318–2323, 2011.Navid Samavati, Michael Velec, and Kristy K. Brock. Effect of deformable registration uncertainty on lung sbrt dose accumulation. Medical Physics, 43(1):233–240, 2016.Francisco J. Salguero, Nahla K. Saleh-Sayah, Chenyu Yan, and Jeffrey V. Siebers. 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Advances in Radiation Oncology, 4(1):177–185, 2019.AdministradoresGrupos comunitariosInvestigadoresReceptores de fondos federales y solicitantesORIGINAL1098784037.2022.pdf1098784037.2022.pdfTesis de Maestría en Física Médicaapplication/pdf5784800https://repositorio.unal.edu.co/bitstream/unal/82622/2/1098784037.2022.pdf76638870744ea38d306fddcef4456464MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/82622/3/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD53THUMBNAIL1098784037.2022.pdf.jpg1098784037.2022.pdf.jpgGenerated Thumbnailimage/jpeg4412https://repositorio.unal.edu.co/bitstream/unal/82622/4/1098784037.2022.pdf.jpg2e23ddcc5cdef34994453c092b418ae4MD54unal/82622oai:repositorio.unal.edu.co:unal/826222024-08-12 01:59:58.538Repositorio Institucional Universidad Nacional de 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

Validation of deformable image registration based on contours for dose accumulation in external beam radiotherapy

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