Advertisement

Development of an Analytic Breast Phantom for Quantitative Comparison of Reconstruction Algorithms for Digital Breast Tomosynthesis

  • I. Reiser
  • E. Y. Sidky
  • R. M. Nishikawa
  • X. Pan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)

Abstract

We are developing an analytic breast phantom that allows for quantitative comparison of reconstruction algorithms for digital breast tomosynthesis. The phantom consists of simple shapes and aims at capturing the main features of the breast. Projection data can be computed analytically. We present volumes reconstructed from the phantom data using the filtered backprojection, expectation maximization and total variation algorithms. Our results indicate that the TV algorithm achieves highest contrast for mass lesions and best in-depth resolution.

Keywords

Reconstruction Algorithm Projection Data Digital Breast Tomosynthesis Detector Surface Imaging Geometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Wu, T., Stewart, A., Stanton, M., McCauley, T., Phillips, W., Kopans, D.B., Moore, R.H., Eberhard, J.W., Opsahl-Ong, B., Niklason, L., Williams, M.B.: Tomographic mammography using a limited number of low-dose cone-beam projection images. Med. Phys. 30, 365–380 (2003)CrossRefGoogle Scholar
  2. 2.
    Wu, T., Moore, R.H., Rafferty, E.A., Kopans, D.B.: A comparison of reconstruction algorithms for breast tomosynthesis. Med. Phys. 31, 2636–2647 (2004)CrossRefGoogle Scholar
  3. 3.
    Ren, B., Ruth, C., Stein, J., Smith, A., Shaw, I., Jing, Z.: Design and performance of the prototype full field breast tomosynthesis system with selenium-based flat panel detector. In: Proc. SPIE, vol. 5745, p. 550 (2005)Google Scholar
  4. 4.
    Bissonnette, M., Hansroul, M., Masson, E., Savard, S., Cadieux, S., Warmoes, P., Gravel, D., Agopyan, J., Polischuk, B., Haerer, W., Mertelmeier, T., Lo, J.Y., Chen, Y., Dobbins III, J.T., Jesneck, J.L., Singh, S.: Digital tomosynthesis using an amorphous selenium flat panel detector. In: Proc. SPIE, vol. 5745, p. 529 (2005)Google Scholar
  5. 5.
    Lange, K., Fessler, J.A.: Globally convergent algorithms for maximum a posteriori transmission tomography. IEEE Trans. Med. Imag. 4, 1338–1430 (1995)Google Scholar
  6. 6.
    Goodfrey, D.J., Warp, R.J., Dobbins III, J.T.: Optimization of matrix inversion tomosynthesis. In: Proc. SPIE, vol. 4320, pp. 696–704 (2001)Google Scholar
  7. 7.
    Johns, P.C., Yaffe, M.J.: X-ray characterisation of normal and neoplastic breast tissues. Phys. Med. Biol. 32, 675–695 (1987)CrossRefGoogle Scholar
  8. 8.
    Barrett, H.H., Myers, K.J.: Foundations of Image Science. Wiley Interscience, Chichester (2003)Google Scholar
  9. 9.
    Sidky, E.Y., Kao, C.M., Pan, X.: Accurate image reconstruction from few-views and limited-angle data in divergent-beam CT. Journal of X-Ray Science and Technology (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • I. Reiser
    • 1
  • E. Y. Sidky
    • 1
  • R. M. Nishikawa
    • 1
  • X. Pan
    • 1
  1. 1.Department of RadiologyThe University of ChicagoChicagoUSA

Personalised recommendations