A Modelling Framework for Evaluation of 2D-Mammography and Breast Tomosynthesis Systems

Planar 2D X-ray mammography is the most common screening technique used for breast cancer detection. Digital breast tomosynthesis (DBT) is a new and emerging technology that overcomes some of the limitations of conventional planar imaging. However, it is important to understand the impact of these two modalities on cancer detection rates and patient recall. Since it is difficult to adequately evaluate different modalities clinically, a collection of modeling tools is introduced in this paper that can be used to emulate the image acquisition process for both modalities. In this paper, we discuss image simulation chains that can be used for the evaluation of 2D-mammography and DBT systems in terms of both technical factors and observer studies.

[1]  R. Siddon.  Fast calculation of the exact radiological path for a three-dimensional CT array. , 1985, Medical physics.

[2]  Thomas Mertelmeier,et al.  Optimizing filtered backprojection reconstruction for a breast tomosynthesis prototype device , 2006, SPIE Medical Imaging.

[3]  Andrew D. A. Maidment,et al.  Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm. , 2011, Medical physics.

[4]  Alaleh Rashidnasab,et al.  Realistic simulation of breast mass appearance using random walk , 2012, Medical Imaging.

[5]  T. R. Fewell,et al.  Molybdenum, rhodium, and tungsten anode spectral models using interpolating polynomials with application to mammography. , 1997, Medical physics.

[6]  Alaleh Rashidnasab,et al.  Modeling realistic breast lesions using diffusion limited aggregation , 2012, Medical Imaging.

[7]  Kenneth C. Young,et al.  Conversion of mammographic images to appear with the noise and sharpness characteristics of a different detector and x-ray system. , 2012, Medical physics.

[8]  J. H. Hubbell,et al.  XCOM : Photon Cross Sections Database , 2005 .

[9]  H. Bosmans,et al.  The simulation of 3D microcalcification clusters in 2D digital mammography and breast tomosynthesis. , 2011, Medical physics.

[10]  Kenneth C. Young,et al.  A fast scatter field estimator for digital breast tomosynthesis , 2012, Medical Imaging.

[11]  D. M. Parkin,et al.  Use of Statistics to Assess the Global Burden of Breast Cancer , 2006, The breast journal.

[12]  Kenneth G. A. Gilhuijs,et al.  Breast tomosynthesis in clinical practice: initial results , 2009, European Radiology.