.: Click here to download :.
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.
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Figure 1. Breast density |
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A simple and effective source code for Breast Density Classification System. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Image Processing Toolbox, Matlab Wavelet Toolbox and Matlab Signal Processing Toolbox are required. |
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Release |
Date |
Major features |
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1.0 |
2013.12.19 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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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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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Breast Density Classification System. Alternatively, you can bestow using our banking coordinates:
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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.
