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Breast cancer produces a high rate of mortality worldwide. Early diagnosis is essential for treatment, however it is difficult to analyse high density breast tissues. Computer-aided diagnosis systems have been proposed to classify the density of mammograms, having as a major challenge to define the features that better represent the images to be classified. In this study, besides comparing them to other techniques, different texture descriptors for the representation of breast tissue density on mammograms are analyzed. We have developed an algorithm that is able to classify mammograms into three classes: Fatty, Fatty-Glandular and Dense-Glanduar. In the experiments, 322 mammograms from MIAS Database are used, and the highest accuracy obtained is 79.39% with Leave-One-Out cross-validation.

Our approach is fully automated and it does not require any manual intervention from user. The proposed approach works in spatial and frequency-related domain and it results extremely robust to noise and background regions, with a high degree of accuracy.

Index Terms: Matlab, source, code, mammography, breast cancer, breast density, texture features, classification, fatty, glandular, dense.

 

 

 

 

 

Figure 1. Breast density



A simple and effective source code for Breast Density Classification System.



Demo code (protected P-files) available for performance evaluation. Matlab Image Processing Toolbox, Matlab Wavelet Toolbox and Matlab Signal Processing Toolbox are required.

Release
Date
Major features
1.0

2013.12.19



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Breast Density Classification System - Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 400 EUROS (less than 560 U.S. Dollars).

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The authors have no relationship or partnership with The Mathworks. All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 2006a. Matlab Image Processing Toolbox, Matlab Wavelet Toolbox and Matlab Signal Processing Toolbox are required. The code provided has to be considered "as is" and it is without any kind of warranty. The authors deny any kind of warranty concerning the code as well as any kind of responsibility for problems and damages which may be caused by the use of the code itself including all parts of the source code.

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