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A robust deformable image registration enhancement method based on radial basis function.

Publication ,  Journal Article
Liang, X; Yin, F-F; Wang, C; Cai, J
Published in: Quant Imaging Med Surg
July 2019

BACKGROUND: To develop and evaluate a robust deformable image registration (DIR) enhancement method based on radial basis function (RBF) expansion. METHODS: To improve DIR accuracy using sparsely available measured displacements, it is crucial to estimate the motion correlation between the voxels. In the proposed method, we chose to derive this correlation from the initial displacement vector fields (DVFs), and represent it in the form of RBF expansion coefficients of the voxels. The method consists of three steps: (I) convert an initial DVF to a coefficient matrix comprising expansion coefficients of the Wendland's RBF; (II) modify the coefficient matrix under the guidance of sparely distributed landmarks to generate the post-enhancement coefficient matrix; and (III) convert the post-enhancement coefficient matrix to the post-enhancement DVF. The method was tested on five DIR algorithms using a digital phantom. 3D registration errors were calculated for comparisons between the pre-/post-enhancement DVFs and the ground-truth DVFs. Effects of the number and locations of landmarks on DIR enhancement were evaluated. RESULTS: After applying the DIR enhancement method, the 3D registration errors per voxel (unit: mm) were reduced from pre-enhancement to post-enhancement by 1.3 (2.4 to 1.1, 54.2%), 0.0 (0.9 to 0.9, 0.0%), 6.1 (8.2 to 2.1, 74.4%), 3.2 (4.7 to 1.5, 68.1%), and 1.7 (2.9 to 1.2, 58.6%) for the five tested DIR algorithms respectively. The average DIR error reduction was 2.5±2.3 mm (percentage error reduction: 51.1%±29.1%). 3D registration errors decreased inverse-exponentially as the number of landmarks increased, and were insensitive to the landmarks' locations in relation to the down-sampling DVF grids. CONCLUSIONS: We demonstrated the feasibility of a robust RBF-based method for enhancing DIR accuracy using sparsely distributed landmarks. This method has been shown robust and effective in reducing DVF errors using different numbers and distributions of landmarks for various DIR algorithms.

Duke Scholars

Published In

Quant Imaging Med Surg

DOI

ISSN

2223-4292

Publication Date

July 2019

Volume

9

Issue

7

Start / End Page

1315 / 1325

Location

China

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 0299 Other Physical Sciences
  • 0205 Optical Physics
  • 0204 Condensed Matter Physics
 

Citation

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MLA
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Liang, X., Yin, F.-F., Wang, C., & Cai, J. (2019). A robust deformable image registration enhancement method based on radial basis function. Quant Imaging Med Surg, 9(7), 1315–1325. https://doi.org/10.21037/qims.2019.07.05
Liang, Xiao, Fang-Fang Yin, Chunhao Wang, and Jing Cai. “A robust deformable image registration enhancement method based on radial basis function.Quant Imaging Med Surg 9, no. 7 (July 2019): 1315–25. https://doi.org/10.21037/qims.2019.07.05.
Liang X, Yin F-F, Wang C, Cai J. A robust deformable image registration enhancement method based on radial basis function. Quant Imaging Med Surg. 2019 Jul;9(7):1315–25.
Liang, Xiao, et al. “A robust deformable image registration enhancement method based on radial basis function.Quant Imaging Med Surg, vol. 9, no. 7, July 2019, pp. 1315–25. Pubmed, doi:10.21037/qims.2019.07.05.
Liang X, Yin F-F, Wang C, Cai J. A robust deformable image registration enhancement method based on radial basis function. Quant Imaging Med Surg. 2019 Jul;9(7):1315–1325.

Published In

Quant Imaging Med Surg

DOI

ISSN

2223-4292

Publication Date

July 2019

Volume

9

Issue

7

Start / End Page

1315 / 1325

Location

China

Related Subject Headings

  • 5102 Atomic, molecular and optical physics
  • 4003 Biomedical engineering
  • 0299 Other Physical Sciences
  • 0205 Optical Physics
  • 0204 Condensed Matter Physics