Skip to main content
SpringerLink
Log in

Deformable Registration of Chest Radiographs Using B-spline Based Method with Modified Residual Complexity

  • Published:
Journal of Shanghai Jiaotong University (Science) Aims and scope Submit manuscript

Abstract

Accurate registration of chest radiographs plays an increasingly important role in medical applications. However, most current intensity-based registration methods rely on the assumption of intensity conservation that is not suitable for alignment of chest radiographs. In this study, we propose a novel algorithm to match chest radiographs, for which the conventional residual complexity (RC) is modified as the similarity measure and the cubic B-spline transformation is adopted for displacement estimation. The modified similarity measure is allowed to incorporate the neighborhood influence into variation of intensity in a justified manner of the weight, while the transformation is implemented with a registration framework of pyramid structure. The results show that the proposed algorithm is more accurate in registration of chest radiographs, compared with some widely used methods such as the sum-of-squared-differences (SSD), correlation coefficient (CC) and mutual information (MI) algorithms, as well as the conventional RC approaches.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. ISHIDA T, KATSURAGAWA S, NAKAMURA K, et al. Iterative image warping technique for temporal subtraction of sequential chest radiographs to detect interval change [J]. Medical Physics, 1999, 26(7): 1320–1329.

    Article  Google Scholar 

  2. LI M, CASTILLO E, LUO H Y, et al. Deformable image registration for temporal subtraction of chest radiographs [J]. International Journal of Computer Assisted Radiology & Surgery, 2014, 9(4): 513–522.

    Article  Google Scholar 

  3. HILL D L G, BATCHELOR P G, HOLDEN M, et al. Medical image registration [J]. Physics in Medicine and Biology, 2001, 46(3): 1–45.

    Article  Google Scholar 

  4. ZITOVA B, FLUSSER J. Image registration methods: A survey [J]. Image and Vision Computing, 2003, 21(11): 977–1000.

    Article  Google Scholar 

  5. HARRIS C G, STEPHENS M. A combined corner and edge detector [C]// Proceedings of the 4th Alvey Vision Conference. Alvey, UK: [s.n.], 1988: 147–151.

    Google Scholar 

  6. SMITH S M, BRADY J M. SUSAN: A new approach to low level image processing [J]. International Journal of Computer Vision, 1997, 23(1): 45–78.

    Article  Google Scholar 

  7. MORADI M, ABOLMAESUMI P. Medical image registration based on distinctive image features from scale-invariant (SIFT) key-points [J]. International Congress Series, 2005, 1281: 1292.

    Article  Google Scholar 

  8. SANG Q, ZHANG J Z, YU Z Y. Robust non-rigid point registration based on feature-dependant finite mixture model [J]. Pattern Recognition Letters, 2013, 34(13): 1557–1565.

    Article  Google Scholar 

  9. CRUM W R, HARTKENS T, HILL D L G. Nonrigid image registration: Theory and practice [J]. The British Journal of Radiology, 2004, 77(Sup 2): 140–153.

    Google Scholar 

  10. BROIT C. Optimal registration of deformed images [J]. Acta Obstetrica Et Gynaecologica Japonica, 1981, 39(4): 556–562.

    Google Scholar 

  11. CHRISTENSEN G E, RABBITT R D, MILLER M I. Deformable templates using large deformation kinematics [J]. IEEE Transactions on Image Processing, 1996, 5(10): 1435–1447.

    Article  Google Scholar 

  12. THIRION J P. Image matching as a diffusion process: An analogy with Maxwell’s demons [J]. Medical Image Analysis, 1998, 2(3): 243–260.

    Article  Google Scholar 

  13. YANG J, WANG Y T, TANG S Y, et al. Multiresolution elastic registration of X-ray angiography images using thin-plate spline [J]. IEEE Transactions on Nuclear Science, 2007, 54(1): 152–166.

    Article  Google Scholar 

  14. MYRONENKO A, SONG X B. Intensity-based image registration by minimizing residual complexity [J]. IEEE Transactions on Medical Imaging, 2010, 29(11): 1882–1891.

    Article  Google Scholar 

  15. NOCEDAL J, WRIGHT S J. Numerical optimization [M]. Berlin, Germany: Springer Science & Business Media, 2006.

    MATH  Google Scholar 

  16. KLEIN S, STARING M, PLUIM J P W. Evaluation of optimization methods for nonrigid medical image registration using mutual information and B-splines [J]. IEEE Transactions on Image Processing, 2007, 16(12): 2879–2890.

    Article  MathSciNet  Google Scholar 

  17. PENNEY G P, WEESE J, LITTLE J A, et al. A comparison of similarity measures for use in 2D-3D medical image registration [C]//Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention. Berlin, Germany: Springer, 1998: 1153–1161.

    Google Scholar 

  18. STRANG G. The discrete cosine transform [J]. SIAM Review, 1999, 41(1): 135–147.

    Article  MathSciNet  MATH  Google Scholar 

  19. BROWN L G. A survey of image registration techniques [J]. ACM Computing Surveys, 1992, 24(4): 325–376.

    Article  Google Scholar 

  20. MAES F, COLLIGNON A, VANDERMEULEN D, et al. Multimodality image registration by maximization of mutual information [J]. IEEE Transactions on Medical Imaging, 1997, 16(2): 187–198.

    Article  Google Scholar 

  21. CHEN Z, HAYKIN S. On different facets of regularization theory [J]. Neural Computation, 2002, 14(12): 2791–2846.

    Article  MATH  Google Scholar 

  22. RUECKERT D, SONODA L I, HAYES C, et al. Nonrigid registration using free-form deformations: Application to breast MR images [J]. IEEE Transactions on Medical Imaging, 1999, 18(8): 712–721.

    Article  Google Scholar 

  23. HOLDEN M. A review of geometric transformations for nonrigid body registration [J]. IEEE Transactions on Medical Imaging, 2008, 27(1): 111–128.

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

    Zhikang Xiang  (相志康), Min Li  (李敏), Liang Xiao  (肖亮), Zhichao Lian  (练智超) & Zhihui Wei  (韦志辉)

Authors
  1. Zhikang Xiang  (相志康)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Min Li  (李敏)
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liang Xiao  (肖亮)
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhichao Lian  (练智超)
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhihui Wei  (韦志辉)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Min Li  (李敏).

Additional information

Foundation item: the Fundamental Research Funds for the Central Universities of China (No. 30918011104), the National Natural Science Foundation of China (Nos. 61501241 and 61571230), the Natural Science Foundation of Jiangsu Province (No. BK20150792), the Foundation of Shandong Provincial Key Laboratory of Digital Medicine and Computer assisted Surgery (No. SDKL-DMCAS-2018-04), the China Postdoctoral Science Foundation (No. 2015M570450), and the Visiting Scholar Foundation of Key Laboratory of Biorheological Science and Technology (Chongqing University) of Ministry of Education (No. CQKLBST-2018-011)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiang, Z., Li, M., Xiao, L. et al. Deformable Registration of Chest Radiographs Using B-spline Based Method with Modified Residual Complexity. J. Shanghai Jiaotong Univ. (Sci.) 24, 226–232 (2019). https://doi.org/10.1007/s12204-019-2056-8

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12204-019-2056-8

Key words

CLC number

Document code

Search

Navigation