========================================================

	   Dataset: MM-S2TXTR-F03

	Textural features of mammographic masses
	      Greece, Feb.2003
 
	        Release Notes

	Copyright (c) 2016 by Harris V. Georgiou

========================================================
   Release:     Aug 3, 2016

   - Version:  1.1a
   - Format:   .mat
========================================================


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.

_______________________________________________
WHAT'S IN THIS PACKAGE?

-  Overview
-  Available file formats
-  Files and Datasets
-  License Agreement

_______________________________________________
OVERVIEW

Localized texture analysis of breast tissue on mammograms is an issue of
major importance in mass characterization. This material aims to the 
establishment of a quantitative approach of mammographic masses texture 
classification based on these datasets of the extracted textural features.

This package contains an extensive set of textural feature datasets, in 
multiple configurations and scales, constructing compact sets of textural 
"signatures" for benign and malignant cases of tumors in mammograms.
The datasets refer to 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 files also include the full texture data of 7,000-13,000 sampling "boxes"
of sizes 20 and 50 pixels, as well as complete-mass and borderline-only
sampling areas. 

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_texture_directory.pdf).

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)

* M. Mavroforakis, H. Georgiou, et. al.
"Mammographic Masses Characterization, based on Localized Texture and 
Dataset Fractal Analysis, Using Linear, Neural and SVM Classifiers",
Artificial Intelligence in Medicine, Vol 37 (2) (2006) 145-162. 
(doi:10.1016/j.artmed.2006.03.002)

_______________________________________________
AVAILABLE FILE FORMATS

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

*.mat	: Matlab/Octave native data file (workspace)

_______________________________________________
FILES AND DATASETS

Root folder:	MM-S2TXTR-F03\

	(For full description see: S2_data_texture_directory.pdf)

_______________________________________________
LICENSE AGREEMENT

This material was produced primarily for academic research and educational purposes. 
Downloading and using this material implies acceptance of the Creative Commons
License: Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA), 2016.
* http://creativecommons.org/licenses/by-nc-sa/4.0/

Copyright (c) 2016 by Harris V. Georgiou (MSc,PhD) -- http://xgeorgio.info


--

