Evaluation of CT to CBCT non-linear dense anatomical block matching registration for prostate patients

[1]  Dualta McQuaid,et al.  Assessment of fully-automated atlas-based segmentation of novel oral mucosal surface organ-at-risk. , 2016, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[2]  Rolf Bendl,et al.  Accuracy quantification of a deformable image registration tool applied in a clinical setting , 2014, Journal of applied clinical medical physics.

[3]  Nicholas Hardcastle,et al.  Accuracy of deformable image registration for contour propagation in adaptive lung radiotherapy , 2013, Radiation oncology.

[4]  Jinkoo Kim,et al.  A novel approach for establishing benchmark CBCT/CT deformable image registrations in prostate cancer radiotherapy. , 2013, Physics in medicine and biology.

[5]  Matthias Guckenberger,et al.  A multi-institution evaluation of deformable image registration algorithms for automatic organ delineation in adaptive head and neck radiotherapy , 2012, Radiation oncology.

[6]  Sébastien Ourselin,et al.  Toward adaptive radiotherapy for head and neck patients: Uncertainties in dose warping due to the choice of deformable registration algorithm. , 2015, Medical physics.

[7]  Mattias P. Heinrich,et al.  Advances and challenges in deformable image registration: From image fusion to complex motion modelling , 2016, Medical Image Anal..

[8]  H. Marshall,et al.  A method for quantitative analysis of regional lung ventilation using deformable image registration of CT and hybrid hyperpolarized gas/1H MRI , 2014, Physics in medicine and biology.

[9]  Sahar Ahmad,et al.  Topology preserving non-rigid image registration using time-varying elasticity model for MRI brain volumes , 2015, Comput. Biol. Medicine.

[10]  Fréderic Duprez,et al.  Deformation field validation and inversion applied to adaptive radiation therapy , 2013, Physics in medicine and biology.

[11]  Siyong Kim,et al.  Deformable image registration in radiation therapy , 2017, Radiation oncology journal.

[12]  A Noel,et al.  Evaluation of the Block Matching deformable registration algorithm in the field of head-and-neck adaptive radiotherapy. , 2014, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[13]  Raj Shekhar,et al.  Accurate tracking of tumor volume change during radiotherapy by CT-CBCT registration with intensity correction , 2016, SPIE Medical Imaging.

[14]  Terry M Peters,et al.  Generalized 3D nonlinear transformations for medical imaging: an object-oriented implementation in VTK. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[15]  Jesper Carl,et al.  A new method to validate thoracic CT-CT deformable image registration using auto-segmented 3D anatomical landmarks , 2015, Acta oncologica.

[16]  Kavitha Srinivasan,et al.  Cone Beam Computed Tomography for Adaptive Radiotherapy Treatment Planning , 2014 .

[17]  Guozhi Tao,et al.  Symmetric inverse consistent nonlinear registration driven by mutual information , 2009, Comput. Methods Programs Biomed..

[18]  J. Pouliot,et al.  The need for application-based adaptation of deformable image registration. , 2012, Medical physics.

[19]  Murat Surucu,et al.  Evaluation of Deformable Image Registration-Based Contour Propagation From Planning CT to Cone-Beam CT , 2017, Technology in cancer research & treatment.

[20]  João Manuel R S Tavares,et al.  Medical image registration: a review , 2014, Computer methods in biomechanics and biomedical engineering.

[21]  Linghong Zhou,et al.  CT to cone-beam CT deformable registration with simultaneous intensity correction , 2012, Medical physics.

[22]  X. Gu,et al.  Comprehensive evaluation of ten deformable image registration algorithms for contour propagation between CT and cone-beam CT images in adaptive head & neck radiotherapy , 2017, PloS one.

[23]  Sébastien Ourselin,et al.  Toward adaptive radiotherapy for head and neck patients: Feasibility study on using CT-to-CBCT deformable registration for "dose of the day" calculations. , 2014, Medical physics.

[24]  W. Tomé,et al.  On the dosimetric effect and reduction of inverse consistency and transitivity errors in deformable image registration for dose accumulation. , 2011, Medical physics.

[25]  X Zhen,et al.  Evaluation of deformable image registration for contour propagation between CT and cone-beam CT images in adaptive head and neck radiotherapy. , 2016, Technology and health care : official journal of the European Society for Engineering and Medicine.

[26]  Xiaoning Pan,et al.  A fully automated method for CT-on-rails-guided online adaptive planning for prostate cancer intensity modulated radiation therapy. , 2013, International journal of radiation oncology, biology, physics.

[27]  J. Seong,et al.  Re-Irradiation of Hepatocellular Carcinoma: Clinical Applicability of Deformable Image Registration , 2015, Yonsei medical journal.

[28]  Xiao Han,et al.  Artifact reduction in short-scan CBCT by use of optimization-based reconstruction , 2016, Physics in medicine and biology.

[29]  Di Yan,et al.  MR image‐based synthetic CT for IMRT prostate treatment planning and CBCT image‐guided localization , 2016, Journal of applied clinical medical physics.

[30]  M. Chao,et al.  Feasibility Study on Deformable Image Registration for Lung SBRT Patients for Dose-Driven Adaptive Therapy , 2015 .

[31]  R. Berenguer,et al.  The influence of the image registration method on the adaptive radiotherapy. A proof of the principle in a selected case of prostate IMRT. , 2018, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[32]  Sébastien Ourselin,et al.  Inverse-Consistent Symmetric Free Form Deformation , 2012, WBIR.

[33]  Huazhong Shu,et al.  Accelerated gradient-based free form deformable registration for online adaptive radiotherapy. , 2015, Physics in medicine and biology.

[34]  Suguru Dobashi,et al.  Evaluation of various deformable image registration algorithms for thoracic images , 2013, Journal of radiation research.

[35]  Max A. Viergever,et al.  Adaptive Stochastic Gradient Descent Optimisation for Image Registration , 2009, International Journal of Computer Vision.

[36]  Takeshi Ebara,et al.  Assessing cumulative dose distributions in combined radiotherapy for cervical cancer using deformable image registration with pre-imaging preparations , 2014, Radiation oncology.

[37]  Nikos Paragios,et al.  Deformable Medical Image Registration: A Survey , 2013, IEEE Transactions on Medical Imaging.

[38]  Pascal Haigron,et al.  Roles of Deformable Image Registration in adaptive RT: From Contour propagation to dose monitoring , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[39]  S. Mali,et al.  Adaptive Radiotherapy for Head Neck Cancer , 2016, Journal of Maxillofacial and Oral Surgery.

[40]  Max A. Viergever,et al.  elastix: A Toolbox for Intensity-Based Medical Image Registration , 2010, IEEE Transactions on Medical Imaging.

[41]  J. Seuntjens,et al.  Implementation of an efficient Monte Carlo calculation for CBCT scatter correction: phantom study , 2015, Journal of applied clinical medical physics.

[42]  Indrin J Chetty,et al.  Deformable image registration based automatic CT-to-CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting. , 2014, Medical physics.

[43]  Gregory C Sharp,et al.  Evaluation of deformable registration of patient lung 4DCT with subanatomical region segmentations. , 2008, Medical physics.

[44]  Andras Lasso,et al.  SlicerRT: radiation therapy research toolkit for 3D Slicer. , 2012, Medical physics.

[45]  Xun Jia,et al.  Joint CT/CBCT deformable registration and CBCT enhancement for cancer radiotherapy , 2013, Medical Image Anal..

[46]  Maria Thor,et al.  Deformable image registration for contour propagation from CT to cone-beam CT scans in radiotherapy of prostate cancer , 2011, Acta oncologica.

[47]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[48]  Haijo Jung,et al.  Evaluation of various deformable image registrations for point and volume variations , 2015 .

[49]  J. Molloy,et al.  CBCT-based dosimetric verification and alternate planning techniques to reduce the normal tissue dose in SBRT of lung patients , 2015 .

[50]  Ernesto Mainegra-Hing,et al.  Patient-specific scatter correction in clinical cone beam computed tomography imaging made possible by the combination of Monte Carlo simulations and a ray tracing algorithm , 2013, Acta oncologica.

[51]  M. Stock,et al.  Performance validation of deformable image registration in the pelvic region , 2013, Journal of radiation research.