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Evaluation of accuracy of B-spline transformation-based deformable image registration with different parameter settings for thoracic images.
- Source :
-
Journal of radiation research [J Radiat Res] 2014 Nov; Vol. 55 (6), pp. 1163-70. Date of Electronic Publication: 2014 Jul 22. - Publication Year :
- 2014
-
Abstract
- Deformable image registration (DIR) is fundamental technique for adaptive radiotherapy and image-guided radiotherapy. However, further improvement of DIR is still needed. We evaluated the accuracy of B-spline transformation-based DIR implemented in elastix. This registration package is largely based on the Insight Segmentation and Registration Toolkit (ITK), and several new functions were implemented to achieve high DIR accuracy. The purpose of this study was to clarify whether new functions implemented in elastix are useful for improving DIR accuracy. Thoracic 4D computed tomography images of ten patients with esophageal or lung cancer were studied. Datasets for these patients were provided by DIR-lab (dir-lab.com) and included a coordinate list of anatomical landmarks that had been manually identified. DIR between peak-inhale and peak-exhale images was performed with four types of parameter settings. The first one represents original ITK (Parameter 1). The second employs the new function of elastix (Parameter 2), and the third was created to verify whether new functions improve DIR accuracy while keeping computational time (Parameter 3). The last one partially employs a new function (Parameter 4). Registration errors for these parameter settings were calculated using the manually determined landmark pairs. 3D registration errors with standard deviation over all cases were 1.78 (1.57), 1.28 (1.10), 1.44 (1.09) and 1.36 (1.35) mm for Parameter 1, 2, 3 and 4, respectively, indicating that the new functions are useful for improving DIR accuracy, even while maintaining the computational time, and this B-spline-based DIR could be used clinically to achieve high-accuracy adaptive radiotherapy.<br /> (© The Author 2014. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.)
- Subjects :
- Algorithms
Four-Dimensional Computed Tomography
Humans
Phantoms, Imaging
Radiography, Thoracic
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Image-Guided
Software
Esophageal Neoplasms diagnostic imaging
Esophageal Neoplasms radiotherapy
Lung Neoplasms diagnostic imaging
Lung Neoplasms radiotherapy
Radiographic Image Interpretation, Computer-Assisted methods
Subjects
Details
- Language :
- English
- ISSN :
- 1349-9157
- Volume :
- 55
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- Journal of radiation research
- Publication Type :
- Academic Journal
- Accession number :
- 25053349
- Full Text :
- https://doi.org/10.1093/jrr/rru062