TY - JOUR

T1 - Automated effect-specific mammographic pattern measures

AU - Raundahl, Jakob

AU - Loog, Marco

AU - Pettersen, Paola

AU - Tankó, Lazlo B.

AU - Nielsen, Mads

PY - 2008/8/1

Y1 - 2008/8/1

N2 - We investigate the possibility to develop methodologies for assessing effect specific structural changes of the breast tissue using a general statistical machine learning framework. We present an approach of obtaining objective mammographic pattern measures quantifying a specific biological effect, such as hormone replacement therapy (HRT). We compare results using this approach to using standard density measures. We show that the proposed method can quantify both age related effects and effects caused by HRT. Age effects are significantly detected by our method where standard methodologies fail. The separation of HRT subpopulations using our approach is comparable to the best methodology, which is interactive.

AB - We investigate the possibility to develop methodologies for assessing effect specific structural changes of the breast tissue using a general statistical machine learning framework. We present an approach of obtaining objective mammographic pattern measures quantifying a specific biological effect, such as hormone replacement therapy (HRT). We compare results using this approach to using standard density measures. We show that the proposed method can quantify both age related effects and effects caused by HRT. Age effects are significantly detected by our method where standard methodologies fail. The separation of HRT subpopulations using our approach is comparable to the best methodology, which is interactive.

U2 - 10.1109/TMI.2008.917245

DO - 10.1109/TMI.2008.917245

M3 - Journal article

C2 - 18672423

VL - 27

SP - 1054

EP - 1060

JO - I E E E Transactions on Medical Imaging

JF - I E E E Transactions on Medical Imaging

SN - 0278-0062

IS - 8

ER -