<div class="sc-jegwdG lhLRCf"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-davvxH eCVTlP"><div class="sc-jCNfQM ikRdXB"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-gVIFzB gQKGyV"><h3>Content</h3>

<p>The data is images and labels / annotations for mammography scans. More about the database can be found at <a rel="noreferrer nofollow" aria-label="MIAS (opens in a new tab)" target="_blank" href="http://peipa.essex.ac.uk/info/mias.html">MIAS</a>. The 'Preview' kernel shows how the Info.txt and PGM files can be parsed correctly.</p>

<h3>Labels</h3>

<ul>

<li><p>1st column:<br>

MIAS database reference number.</p></li>

<li><p>2nd column:<br>

Character of background tissue:<br>

F  Fatty<br>

G  Fatty-glandular<br>

D  Dense-glandular</p></li>

<li><p>3rd column:<br>

Class of abnormality present:<br>

CALC  Calcification<br>

CIRC  Well-defined/circumscribed masses<br>

SPIC  Spiculated masses<br>

MISC  Other, ill-defined masses<br>

ARCH  Architectural distortion<br>

ASYM  Asymmetry<br>

NORM  Normal</p></li>

<li><p>4th column:<br>

Severity of abnormality;<br>

B  Benign<br>

M  Malignant</p></li>

<li><p>5th, 6th columns:<br>

x,y image-coordinates of centre of abnormality.</p></li>

<li><p>7th column:<br>

Approximate radius (in pixels) of a circle enclosing the abnormality.<br>

There are also several things you should note:<br>

The list is arranged in pairs of films, where each pair represents the left (even filename numbers) and right mammograms (odd filename numbers) of a single patient.<br>

The size of all the images is 1024 pixels x 1024 pixels. The images have been centered in the matrix.<br>

When calcifications are present, centre locations and radii apply to clusters rather than individual calcifications. Coordinate system origin is the bottom-left corner.<br>

In some cases calcifications are widely distributed throughout the image rather than concentrated at a single site. In these cases centre locations and radii are inappropriate and have been omitted.</p></li>

</ul>

<h3>Acknowledgements/LICENCE</h3>

<p>MAMMOGRAPHIC IMAGE ANALYSIS SOCIETY<br>

                    MiniMammographic Database<br>

                      LICENCE AGREEMENT<br>

This is a legal agreement between you, the end user and the<br>

Mammographic Image Analysis Society ("MIAS"). Upon installing the <br>

MiniMammographic database (the "DATABASE") on your system you are<br>

agreeing to be bound by the terms of this Agreement.</p>

<ol>

<li>GRANT OF LICENCE<br>

MIAS grants you the right to use the DATABASE, for research purposes <br>

ONLY. For this purpose, you may edit, format, or otherwise modify the<br>

DATABASE provided that the unmodified portions of the DATABASE included<br>

in a modified work shall remain subject to the terms of this Agreement.</li>

<li>COPYRIGHT<br>

The DATABASE is owned by MIAS and is protected by United Kingdom<br>

copyright laws, international treaty provisions and all other<br>

applicable national laws. Therefore you must treat the DATABASE<br>

like any other copyrighted material. If the DATABASE is used in any<br>

publications then reference must be made to the DATABASE within that<br>

publication.</li>

<li>OTHER RESTRICTIONS<br>

You may not rent, lease or sell the DATABASE.</li>

<li>LIABILITY<br>

To the maximum extent permitted by applicable law, MIAS shall not<br>

be liable for damages, other than death or personal injury,<br>

whatsoever (including without limitation, damages for negligence,<br>

loss of business, profits, business interruption, loss of<br>

business information, or other pecuniary loss) arising out of the<br>

use of or inability to use this DATABASE, even if MIAS has been<br>

advised of the possibility of such damages. In any case, MIAS's<br>

entire liability under this Agreement shall be limited to the<br>

amount actually paid by you or your assignor, as the case may be,<br>

for the DATABASE.</li>

</ol>

<h3>Inspiration</h3>

<p>Automatically finding lesions would be a very helpful tool for physicians, also predicting malignancy based on a found/marked lesion</p></div></div></div>