Semi-automatic Reference Standard Construction for Quantitative Evaluation of Lung CT Registration

Keywords

Computer science, Artificial intelligence, Computer vision, Matching (statistics), Set (abstract data type)

References

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• Comparison of different follow-up lung registration methods with and without segmentationThomas Blaffert, Rafael Wiemker — 2004
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• Distributing many points on a sphereEdward B. Saff, Arno B. J. Kuijlaars — 1997
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• Automatic lung segmentation for accurate quantitation of volumetric X-ray CT imagesShicheng Hu, Eric A. Hoffman, Joseph M. Reinhardt — 2001
• Optimization of mutual information for multiresolution image registrationMichaël Unser, P. Thévenaz — 2000
• Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-SplinesStefan Klein, Marius Staring, Josien P. W. Pluim — 2007
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Cited by

• Approximation de l'Information Mutuelle basée sur le développement d'Edgeworth : application au recalage d'images médicales.Mathieu Rubeaux — 2011
• Mass preserving image registration for lung CTУпадышев Николай Васильевич — 2012
• Detection of Time-Varying Structures by Large Deformation Diffeomorphic Metric Mapping to Aid Reading of High-Resolution CT Images of the LungRyo Sakamoto, Susumu Mori, Michael I. Miller — 2014
• Framework for reporting non-rigid image registration performanceH. Choi — 2011
• Registration-based regional lung mechanical analysisKai Ding — 2008
• Regional pulmonary function analysis using image registrationKaifang Du — 2011
• MDCT-based dynamic, subject-specific lung models via image registration for CFD-based interrogation of regional lung functionYoubing Yin — 2011
• Selecting registration schemes in case of interstitial lung disease follow-up in CT.Georgios Vlachopoulos, Panayiotis Korfiatis, Spyros Skiadopoulos — 2015
• Analysis of Three-Dimensional Aerosol Deposition in Pharmacologically Relevant Terms: Beyond Black or White ROIsElliot Greenblatt, Tilo Winkler, R. Scott Harris — 2015
• Patient specific respiratory motion modeling using a limited number of 3D lung CT imagesXue-Li Cui, Xin Gao, Wei Xia — 2014
• Regional lung function and mechanics using image registrationKai Ding — 2010
• Lung nodule modeling and detection for computerized image analysis of low dose CT imaging of the chest.Amal Farag — 2009
• An automatic registration method for pre- and post-interventional CT images for assessing treatment success in liver RFA treatment.Ha Manh Luu, Wiro J. Niessen, Theo van Walsum — 2015
• Spatiotemporal motion estimation for respiratory-correlated imaging of the lungs.Jef Vandemeulebroucke, Simon Rit, Jan Kybic — 2010
• Tensor grid based image registration with application to ventilation estimation on 4D CT lung dataHeike Ruppertshofen, Sven Kabus, Bernd Fischer — 2010
• Effective Volumetric Feature Modeling and Coarse Correspondence via Improved 3DSIFT and Spectral MatchingPeizhi Chen, Xin Li — 2014
• A cubic B-spline-based hybrid registration of lung CT images for a dynamic airway geometric model with large deformationYoubing Yin, Eric A. Hoffman, Kai Ding — 2010
• Evaluation of Feature Detectors and Descriptors for Motion Detection from Aerial VideosChenxu Wang, Shuxiao Li, Yiping Shen — 2014
• Tracking Regional Tissue Volume and Function Change in Lung Using Image RegistrationKunlin Cao, Gary E. Christensen, Kai Ding — 2012
• Mass preserving registration for lung CTVladlena Gorbunova, Pechin Lo, Martine Loeve — 2009

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