Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information
Accurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introdu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2012/285136 |
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| _version_ | 1832550184780824576 |
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| author | Kunlin Cao Kai Ding Joseph M. Reinhardt Gary E. Christensen |
| author_facet | Kunlin Cao Kai Ding Joseph M. Reinhardt Gary E. Christensen |
| author_sort | Kunlin Cao |
| collection | DOAJ |
| description | Accurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introduce a new vesselness similarity cost that improves intensity-only registration. Volumetric CT datasets from six human subjects were used in this study. The performance of four intensity-only registration algorithms was compared with and without adding the vesselness similarity cost function. Matching accuracy was evaluated using landmarks, vessel tree, and fissure planes. The Jacobian determinant of the transformation was used to reveal the deformation pattern of local parenchymal tissue. The average matching error for intensity-only registration methods was on the order of 1 mm at landmarks and 1.5 mm on fissure planes. After adding the vesselness preserving cost function, the landmark and fissure positioning errors decreased approximately by 25% and 30%, respectively. The vesselness cost function effectively helped improve the registration accuracy in regions near thoracic cage and near the diaphragm for all the intensity-only registration algorithms tested and also helped produce more consistent and more reliable patterns of regional tissue deformation. |
| format | Article |
| id | doaj-art-0401416c068a412c98b6a2d7286ff0e6 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-0401416c068a412c98b6a2d7286ff0e62025-02-03T06:07:28ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962012-01-01201210.1155/2012/285136285136Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular InformationKunlin Cao0Kai Ding1Joseph M. Reinhardt2Gary E. Christensen3Biomedical Image Analysis Lab, GE Global Research Center, Niskayuna, NY 12309, USADepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, VA 23298, USADepartment of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242, USADepartment of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242, USAAccurate pulmonary image registration is a challenging problem when the lungs have a deformation with large distance. In this work, we present a nonrigid volumetric registration algorithm to track lung motion between a pair of intrasubject CT images acquired at different inflation levels and introduce a new vesselness similarity cost that improves intensity-only registration. Volumetric CT datasets from six human subjects were used in this study. The performance of four intensity-only registration algorithms was compared with and without adding the vesselness similarity cost function. Matching accuracy was evaluated using landmarks, vessel tree, and fissure planes. The Jacobian determinant of the transformation was used to reveal the deformation pattern of local parenchymal tissue. The average matching error for intensity-only registration methods was on the order of 1 mm at landmarks and 1.5 mm on fissure planes. After adding the vesselness preserving cost function, the landmark and fissure positioning errors decreased approximately by 25% and 30%, respectively. The vesselness cost function effectively helped improve the registration accuracy in regions near thoracic cage and near the diaphragm for all the intensity-only registration algorithms tested and also helped produce more consistent and more reliable patterns of regional tissue deformation.http://dx.doi.org/10.1155/2012/285136 |
| spellingShingle | Kunlin Cao Kai Ding Joseph M. Reinhardt Gary E. Christensen Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information International Journal of Biomedical Imaging |
| title | Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information |
| title_full | Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information |
| title_fullStr | Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information |
| title_full_unstemmed | Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information |
| title_short | Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information |
| title_sort | improving intensity based lung ct registration accuracy utilizing vascular information |
| url | http://dx.doi.org/10.1155/2012/285136 |
| work_keys_str_mv | AT kunlincao improvingintensitybasedlungctregistrationaccuracyutilizingvascularinformation AT kaiding improvingintensitybasedlungctregistrationaccuracyutilizingvascularinformation AT josephmreinhardt improvingintensitybasedlungctregistrationaccuracyutilizingvascularinformation AT garyechristensen improvingintensitybasedlungctregistrationaccuracyutilizingvascularinformation |