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Computer Aid Diagnostic in Mammogram Image Using SUSAN Algorithm and Hierarchical Watershed Transform

  • Chaimae AnibouEmail author
  • Mohammed Nabil Saidi
  • Driss Aboutajdine
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 366)

Abstract

This work is directed toward a conception of a computer aid diagnosis (CAD) system to detect suspicious area in digital mammogram and classify them into normal and abnormal. Original image is preprocessed to separate the breast region from it’s background with pectoral muscle suppression to reduce false positive rate.

The suspicious regions are extracted using a modified SUSAN algorithm, followed by a function that extract dense regions, then an hierarchical watershed transforms applied to detect edges of suspicious regions.

For detected edges Fourier Descriptors are computed and stored as feature vector. A support vector machine is used to classify suspicious regions into normal or abnormal. The proposed system is tested on Mini-Mias database.

Keywords

Mammogram image Preprocessing Segmentation Modified Hierarchical watershed transform Fourier descriptor Support Vector Machine (SVM) 

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Copyright information

© Springer Science+Business Media Singapore 2016

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Authors and Affiliations

  • Chaimae Anibou
    • 1
    Email author
  • Mohammed Nabil Saidi
    • 2
  • Driss Aboutajdine
    • 1
  1. 1.University Mohamed V-AgdalRabatMorocco
  2. 2.INSEARabatMorocco

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