Anatomical Coordinate System for Bilateral Registration of Mammograms

  • Fredrik Georgsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2749)


One important issue when judging mammograms are bilateral comparison. In this paper, someasp ects on the problem of determining coordinates of points inrelation to the anatomy of the breast is given. The points are expressed in anatomical coordinates, making it possible to compare mammograms without doing any geometrical transformations of the images. The method is implemented and is fully automatic.


Geometrical Error Pectoralis Muscle Digitize Mammogram Tissue Movement Bilateral Comparison 
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.


  1. 1.
    G. Borgefors. Distance transformations in digital images. Comput. Vision, Graph ics, Image Processing, 34:344–371, 1986.CrossRefGoogle Scholar
  2. 2.
    R. Chandrasekhar. Systematic Segmentation of Mammograms. PhD thesis, The University of Western Australia, 1996.Google Scholar
  3. 3.
    R. Chandrasekhar and Y. Attikiouzel. A simple method for automatically locating the nipple on mammograms. IEEE Transactions on Medical Imaging, 16:483–494, 5 1997.CrossRefGoogle Scholar
  4. 4.
    R. Chandrasekhar and Y. Attikiouzel. The need to standardize and calibrate databases of digitized mammograms. In N. Karssemeijer, M. Thijsen, J. Hendriks, and L. van Erning, editors, Digital Mammography, Computational Imaging and Vision, pages 403–404. Kluwer Academic Publishers, 1998.Google Scholar
  5. 5.
    F. Georgsson. Differential analysis of bilateral mammograms. In I. Austvoll, editor, Proceedings of The 12th Scandinavian Conference on Image Analysis, pages 70–77. 2001.Google Scholar
  6. 6.
    F. Georgsson and Niclas Björnestål. On the problem of breast compression mod elling. In H.U. Lemke, M.W. Vannier, K. Inamura, A.G. Farman, K. Doi, and J.H. Reiber, editors, Computer Assisted Radiology and Surgery, pages 677–682, 2002.Google Scholar
  7. 7.
    F. Groen and P. Verbeek. Freeman code probabilities of object boundary quantized contours. Computer Graphics and Image Processing, 7:391–402, 1978.CrossRefGoogle Scholar
  8. 8.
    N. Karssemeijer. Automated classification of parenchymal patterns in mammograms. Physics in Medicine and Biology, 43:365–378, 1998.CrossRefGoogle Scholar
  9. 9.
    N. Karssemeijer and G. te Brake. Combining single view features and asymmetry for detection of mass lesions. In N. Karssemeijer, M. Thijsen, J. Hendriks, and L. van Erning, editors, Digital Mammography, Computational Imaging and Vision, pages 95–102. Kluwer Academic Publishers, 1998.Google Scholar
  10. 10.
    S.-L. Kok-Wiles, M. Brady, and R. Highnam. Comparing mammogram pairs for the detection of lesions. In N. Karssemeijer, M. Thijsen, J. Hendriks, and L. van Erning, editors, Digital Mammography, Computational Imaging and Vision, pages 103–110. Kluwer Academic Publishers, 1998.Google Scholar
  11. 11.
    S. Kumar and D. Goldgof. Recovery of global nonrigid motion — a model based approach without point correspondences. In Proceedings of 1996 Conference on Computer Vision and Pattern Recognition. 594–599 1996.Google Scholar
  12. 12.
    T.-K. Lau and W.F. Bischof. Automated detection of breast tumors using the asymmetry approach. Computers and Biomedical Research, 24:273–295, 1991.CrossRefGoogle Scholar
  13. 13.
    A.J. Mendez, P.G. Tahoces, M.J. Lado, M. Souto, and J.J. Vidal. Computer-aided diagnosis: Automatic detection of malignant masses in digitized mammograms. Medical Physics, 25:957–964, 6 1998.CrossRefGoogle Scholar
  14. 14.
    P. Miller and S. Astley. Automated detection of mammographic asymmetry using anatomical features. International Journal of Pattern Recognition and Artificial Intelligence, 7(6): 1461–1476, 1993.CrossRefGoogle Scholar
  15. 15.
    C. Olsén and F. Georgsson. The accuracy of geometric approximation of the mamilla in mammograms. To appear in proceedings of CARS’03, June 2003.Google Scholar
  16. 16.
    M.Y. Sallam and K.W. Bowyer. Registration and difference analysis of corresponding mammogram images. Medical Image Analysis, 3(2):103–118, 1999.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Fredrik Georgsson
    • 1
  1. 1.Department of Computing ScienceUmeå UniversityUmeåSweden

Personalised recommendations