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Feature Point Detection for Non-rigid Registration of Digital Breast Tomosynthesis Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6136))

Abstract

We present an automatic approach to feature point detection that is well-suited to the non-rigid registration of digital breast tomosynthesis images. The approach combines the scale saliency and the continuous intrinsic dimensionality of image structures in order to detect key feature points along the breast boundary and within the breast. These feature points can be used as the control points for polyaffine transformation regularisation. Experimental results show that non-rigid registration driven by such feature points yields good spatial alignment.

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References

  1. Miller, P., Astley, S.: Detection of Breast Asymmetry Using Anatomical Features. In: Proceedings of SPIE, vol. 1905, pp. 433–442 (1993)

    Google Scholar 

  2. Sallam, M., Bowyer, K.: Registration and difference analysis of corresponding mammogram images. Med. Image Anal. 1(1), 73–91 (1996)

    Article  Google Scholar 

  3. Karssemeijer, N., Brake, G.T.: Combining single view features and asymmetry for detection of mass lesions. In: Proc. IWDM, pp. 95–102 (1998)

    Google Scholar 

  4. Marias, K., Behrenbruch, C., Parbhoo, S., Seifalian, A., Brady, M.: A Registration Framework for the Comparison of Mammogram Sequences. IEEE. Trans. Medical. Imaging. 24, 782–790 (2005)

    Article  Google Scholar 

  5. Kadir, T., Brady, M.: Scale, Saliency and Image Description. International Journal of Computer Vision 45(2), 83–105 (2001)

    Article  MATH  Google Scholar 

  6. Felsberg, M., Kalkan, S., Krüger, N.: Continuous Dimensionality Characterization of Image Structures. Image and Vision Computing 27, 628–636 (2009)

    Article  Google Scholar 

  7. Arsigny, V., Pennec, X., Ayache, N.: Polyrigid and polyaffine trasformations: a novel tool to deal with non-rigid deformation - application to the registration of histological slices. Medial Image Analyis 9, 507–523 (2005)

    Article  Google Scholar 

  8. Krüger, N., Felsberg, M.: A continuous formulation of intrinsic dimension. In: British Machine Vision Conference, BMVC (2003)

    Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Zhang, W., Brady, S.M. (2010). Feature Point Detection for Non-rigid Registration of Digital Breast Tomosynthesis Images. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_40

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  • DOI: https://doi.org/10.1007/978-3-642-13666-5_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13665-8

  • Online ISBN: 978-3-642-13666-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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