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K. Cao, G. E. Christensen, K. Ding, and J. M. Reinhardt. Intensity-and-Landmark-Driven, Inverse Consistent, B-Spline Registration and Analysis for Lung Imagery. In M. Brown, M. de Bruijne, B. van Ginneken, A. Kiraly, J.-M. Kuhnigk, C. Lorenz, J. R. McClelland, K. Mori, A. Reeves, and J. M. Reinhardt, eds., Second International Workshop on Pulmonary Image Analysis, pp. 137-148, London, UK, 2009.

Abstract: Lung disease is the number three cause of death in America. Measuring local volume deformation from lung image registration may provide a non-invasive approach for detecting and classifying diseases and provide a means for measuring how these diseases respond to intervention. 3D lung CT images contain easily identifiable landmarks such as airway-tree and vascular-tree branch points that can be used for registration and validation. Intensity-based registration methods complement landmark registration methods by providing dense correspondence information since landmarks only provide sparse correspondence information. Intensity-based registration performs best in regions of strong contrast such as between the lung parenchyma and the chest wall, and between the parenchyma and the blood vessels and larger airways. This paper describes a Landmark, Inverse consistent, Tissue volume preserving, B-Spline (LITS) registration algorithm which can be used to measure local lung volume deformation. This method extends the original tissue volume preserving method by adding landmark information and inverse consistency constraint. LITS registration was applied on three subjects to match lung datasets acquired at functional residual capacity and total lung capacity. The registration errors are small compared to the large overall deformations. Sensitivity analysis was performed by changing node spacing of the parameterization and shows that finer B-Spline lattice setting can reveal more details of the feature deformation.

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Keywords: lung registration

Other publications by: K. Cao, G. E. Christensen, K. Ding, J. M. Reinhardt

Related journal papers:

B. Li, G. E. Christensen, G. McLennan, E. A. Hoffman, and J. M. Reinhardt. Establishing a normative atlas of the human lung: Inter-subject warping and registration of volumetric CT. Acad. Radiol., vol. 10, no. 3, pp. 255-265, 2003. (details)
B. Li, G. E. Christensen, G. McLennan, E. A. Hoffman, and J. M. Reinhardt. Pulmonary CT image registration and warping for tracking tissue deformation during the respiratory cycle through 3-D Consistent Image Registration. Medical Physics, vol. 35, no. 12, pp. 5575-5583, 2008. (details)
J. M. Reinhardt, K. Ding, K. Cao, G. E. Christensen, E. A. Hoffman, and S. V. Bodas. Registration-based estimates of local lung tissue expansion compared to xenon-CT measures of specific ventilation. Medical Image Analysis, vol. 12, no. 6, pp. 752-763, 2008. (details)
J. M. Reinhardt and E. A. Hoffman. Quantitative Pulmonary Imaging: Spatial and Temporal Considerations in HRCT. Acad. Radiol., vol. 5, no. 8, pp. 539-546, 1998. (details)
S. Hu, E. A. Hoffman, and J. M. Reinhardt. Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Trans. Medical Imaging, vol. 20, no. 6, pp. 490-498, 2001. (details)

Related conference papers:

L. Zhang and J. M. Reinhardt. 3D pulmonary CT image registration with a standard lung atlas. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 3978, pp. 67-77, San Diego, CA, 2000. (details)
F. Li, C.-W. Chen, E. A. Hoffman, and J. M. Reinhardt. Evaluation and application of 3D lung warping and registration model using HRCT images. In C.-T. Chen and A. V. Clough, eds., Proc. SPIE Conf. Medical Imaging, vol. 4321, pp. 234-243, San Diego, CA, 2001. (details)
B. Li, G. E. Christensen, J. Dill, E. A. Hoffman, and J. M. Reinhardt. 3-D inter-subject warping and registration of pulmonary CT images for a human lung model. In A. V. Clough and C.-T. Chen, eds., Proc. SPIE Conf. Medical Imaging, vol. 4683, pp. 324-335, San Diego, CA, 2002. (details)
J. de Ryk, E. Namati, J. M. Reinhardt, C. Piker, Y. Xu, L. Liu, E. A. Hoffman, and G. McLennan. A whole organ serial sectioning and imaging system for correlation of pathology to computer tomography. In J.-A. Conchello, C. J. Cogswell, and T. Wilson, eds., Proc. SPIE Conf. Photonics West, vol. 5324, pp. 224-234, San Jose, CA, 2004. (details)
S. Krishnan, K. C. Beck, J. M. Reinhardt, K. A. Carlson, B. A. Simon, R. K. Albert, and E. A. Hoffman. Regional lung ventilation from volumetric CT scans using image warping functions. In 2004 International Symposium on Biomedical Imaging, pp. 792-795, 2004. (details)

Related theses:

K. Ding. Registration-based regional lung mechanical analysis. MS thesis, The University of Iowa, Iowa City, IA, 2008. (details)
B. Li. The construction of a normative human lung atlas by inter-subject registration and warping of CT images. PhD thesis, The University of Iowa, Iowa City, IA, 2004. (details)
Y. Pan. Estimation of regional lung expansion via 3D image registration. MS thesis, The University of Iowa, Iowa City, IA, 2005. (details)
S. Lee. A study of ophthalmologic imaging distortion for retinal image registration and validation. PhD thesis, The University of Iowa, Iowa City, IA, 2008. (details)
S. V. Bodas. Improved association graph matching of intra-patient airway trees. MS thesis, The University of Iowa, Iowa City, IA, 2008. (details)