Abstract
We develop and evaluate an ideal observer for model of the 3D spatial distribution of x-ray attenuation coefficients in the breast. This model relies on thresholding of an underlying Gaussian random field to generate binary objects representing the distribution of adipose and glandular tissue in the breast parenchyma. Our motivation is to evaluate an emerging breast CT device for breast cancer screening. We show how the thresholded Gaussian model fits into the Markov-Chain Monte-Carlo (MCMC) approach for evaluating ideal-observer performance devised by Kupinski et al. [JOSA-A, 2003], and we show some preliminary results indicating that the procedure can be made to generate qualitatively realistic simulations. We demonstrate improved performance of the MCMC ideal observer over a Hotelling linear filter in a small-scale simulation.
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Abbey, C.K., Boone, J.M. (2008). An Ideal Observer for a Model of X-Ray Imaging in Breast Parenchymal Tissue. In: Krupinski, E.A. (eds) Digital Mammography. IWDM 2008. Lecture Notes in Computer Science, vol 5116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70538-3_55
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DOI: https://doi.org/10.1007/978-3-540-70538-3_55
Publisher Name: Springer, Berlin, Heidelberg
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