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IAPR Workshop on Artificial Neural Networks in Pattern Recognition

ANNPR 2012: Artificial Neural Networks in Pattern Recognition pp 127–138Cite as

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Robustness of a CAD System on Digitized Mammograms

Robustness of a CAD System on Digitized Mammograms

  • Antonio García-Manso22,
  • Carlos J. García-Orellana22,
  • Ramón Gallardo-Caballero22,
  • Nico Lanconelli23,
  • Horacio González-Velasco22 &
  • …
  • Miguel Macías-Macías22 
  • Conference paper
  • 1265 Accesses

Part of the Lecture Notes in Computer Science book series (LNAI,volume 7477)

Abstract

In this paper we study the robustness of our CAD system, since this is one of the main factors that determine its quality. A CAD system must guarantee consistent performance over time and in various clinical situations. Our CAD system is based on the extraction of features from the mammographic image by means of Independent Component Analysis, and machine learning classifiers, such as Neural Networks and Support Vector Machine. To measure the robustness of our CAD system we have used the digitized mammograms of the USF’s DDSM database, because this database was built by digitizing mammograms from four different institutions (four different scanner) during more than 10 years. Thus, we can use the mammograms digitized with one scanner to train the system and the remaining to evaluate the performance, what gives us a measure of the robustness of our CAD system.

Keywords

  • ICA
  • NN
  • SVM
  • CAD

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Author information

Authors and Affiliations

  1. Pattern Classification and Image Analysis Group (CAPI), University of Extremadura, Avenida de Elvas, s/n., Badajoz, Extremadura, Spain

    Antonio García-Manso, Carlos J. García-Orellana, Ramón Gallardo-Caballero, Horacio González-Velasco & Miguel Macías-Macías

  2. Medical Imaging Group, Physics Dpt., Bologna University, Viale B., Pichat 6/2, 40127, Bologna, Italy

    Nico Lanconelli

Authors
  1. Antonio García-Manso
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  2. Carlos J. García-Orellana
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  3. Ramón Gallardo-Caballero
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  4. Nico Lanconelli
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  5. Horacio González-Velasco
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  6. Miguel Macías-Macías
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Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler (FBK), 38123, Trento, Italy

    Nadia Mana

  2. Institute of Neural Information Processing, University of Ulm, 89069, Ulm, Germany

    Friedhelm Schwenker

  3. Dipartimento di Ingegneria dell’Informazione, Università di Siena, 53100, Siena, Italy

    Edmondo Trentin

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

García-Manso, A., García-Orellana, C.J., Gallardo-Caballero, R., Lanconelli, N., González-Velasco, H., Macías-Macías, M. (2012). Robustness of a CAD System on Digitized Mammograms. In: Mana, N., Schwenker, F., Trentin, E. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2012. Lecture Notes in Computer Science(), vol 7477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33212-8_12

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  • DOI: https://doi.org/10.1007/978-3-642-33212-8_12

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