P Norm Regularized Breast Tomosynthesis Image Reconstruction

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Abstract
3D cross-sectional images of a breast can be obtained by using limited number of projection data taken from a limited angle with the Digital Breast Tomosynthesis (DBT), which is one of the breast cancer imaging techniques. However, the limited scanning angle and the missing data problem in the DBT cause distortions in reconstructed images. In this study, a regularizer (anisotropic total variation-ATV) that can be used with iterative reconstruction methods has been developed with taking into account DBT system geometry for the missing data problem. At the same time, the minimization of the gradient of the developed ATV, was made with l p norm, which was defined as non-convex depending on the p values. The efficiency of the developed algorithm was evaluated visually and quantitatively using CNR measurements with the help of projection data taken from the real DBT system of the CIRS BR3D phantom. The obtained results confirm that the proposed method provides better contrast resolution to image microcalcifications in a breast tissue.

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