DOI: 10.5281/zenodo.59372
title: Mm-S2Mrph-F03 Morphological Features Of Mammographic Masses, Greece, Feb.2003

description: ========================================================

       Dataset: MM-S2MRPH-F03

    Morphological features of mammographic masses<br>
          Greece, Feb.2003<br>
 <br>
            Release Notes

    Copyright (c) 2016 by Harris V. Georgiou

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   Release:     Aug 3, 2016

   - Version:  1.1a<br>
   - Format:   .mat<br>
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This file contains important information about the current version of the dataset package. Downloading and using this material hints that you accept the EULA/Terms-of-Use (please read carefully).

We welcome your comments and suggestions.

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WHAT'S IN THIS PACKAGE?

-  Overview<br>
-  Available file formats<br>
-  Files and Datasets<br>
-  License Agreement

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OVERVIEW

In localized breast cancers, the morphology and shape characteristics of the detected masses have been established as factors of great importance in the discrimination between fibroadenomas, cysts and carcinomas, due to inherent anatomical differences directly related to malignancy. Approximately 80—85% of diagnostic information is retrieved from the mammographic appearance of the mass.

This package contains efficient datasets of simple yet effective shape features, employed in the original and multi-scaled spectral representations of the boundary, for the characterization of the mammographic mass. Their analysis consists of (a) the investigation of the original radial distance measurements under the complete spectrum of signal analysis, (b) the application of curve feature extractors of morphological characteristics.

The files also include the full radial-distance and spectral registration of 142 localized masses in mammograms, as well as a set of qualitative features that have been proven as of outmost importance regarding the true pathology in each case. For the construction of the raw material for these datasets, 130 of the 142 MLO mammograms containing a mass were selected by an expert physician for digitization, including a total of 46 benign mass cases and 84 mass malignancies of various types (12 were marked 'unreliable').

The digitized mammograms were subsequently transformed digitally to a resolution of 63 mm (400 dpi) at 8-bit gray level, which is consistent with other typical image databases of digitized mammograms that are used as a reference in similar studies.

Detailed information about the files and the structure of the datasets are available in the manifest file (S2_data_morph_directory.pdf).

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AVAILABLE FILE FORMATS

The datasets are available in the following formats (included):

*.mat    : Matlab/Octave native data file (workspace)
description: For further information see:

* M. Mavroforakis, H. Georgiou, et.al.
"Significance Analysis of Qualitative Mammographic Features Using Linear
Classifiers, Neural Networks and Support Vector Machines",
European Journal of Radiology, 54 (2005) 80-89.
(doi:10.1016/j.ejrad.2004.12.015)

* H. Georgiou, M. Mavroforakis, et. al.
"Multi-scaled Morphological Features for the Characterization of
Mammographic Masses Using Statistical Classification Schemes",
Artificial Intelligence in Medicine, 41 (1) (2007), pp.39-55.
(doi:10.1016/j.artmed.2007.06.004)