Classification of Breast Tumors on Digital Mammograms Using Laws’ Texture Features (original) (raw)

Abstract

Mammographic screening is widely used for early detection of breast cancer. Despite the success of screening programs, negative effects should not be underestimated. In many countries, only 15%–40% of detected lesions which are biopsied are subsequently determined malignant. Radiologists might improve their performance, when they could use objective computer-aided diagnosis programs developed with the aim of reducing false positives.

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References

  1. Heath, M., Bowyer, K.W., Kopans, D., et al.: Current status of the Digital Database for Screening Mammography. In: Karsseimeijer, N., Thijssen, M., Hendriks, J., van Erning, L. (eds). Digital Mammography, Kluwer Academic Publishers (1998) 457–460.
    Google Scholar
  2. Tahoces, P.G., Varela, C., Méndez, A.J., Souto, M., Vidal, J.J.: An automatic algorithm for segmentation of mammographic masses on a computerized detection scheme. In: Lemke, H.U., Vannier, M.W., Inamura, K., Farman, A.G., Doi, K. (eds.): Cars 2000. Computer Assisted Radiology and Surgery. Elsevier Science, Amsterdam (2000) 1038.
    Google Scholar
  3. Sahiner, B., Chan, H.P., Petrick, N., Helvie, M.A., Goodsitt, M.M.: Computerized characterization of masses on mammograms: The rubber band straightening transform and texture analysis. Med Phys 25 (1998) 516–526.
    Article Google Scholar

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Authors and Affiliations

  1. Department of Radiology, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain
    Celia Varela
  2. Department of Radiology, University Hospital Nijmegen, PO Box 9101, Nijmegen, 6500 HB, The Netherlands
    Nico Karssemeijer
  3. Department of Electronic and Computer Science, University of Santiago de Compostela, 15782, Santiago de Compostela, Spain
    Pablo G. Tahoces

Authors

  1. Celia Varela
  2. Pablo G. Tahoces

Editor information

Editors and Affiliations

  1. Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
    Wiro J. Niessen & Max A. Viergever &

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© 2001 Springer-Verlag Berlin Heidelberg

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Varela, C., Karssemeijer, N., Tahoces, P.G. (2001). Classification of Breast Tumors on Digital Mammograms Using Laws’ Texture Features. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3\_241

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