Comparison of algorithms for out-of-plane artifacts removal in digital tomosynthesis reconstructions

Digital tomosynthesis is a method of limited angle reconstruction of tomographic images produced at variable heights, on the basis of a set of angular projections taken in an arc around human anatomy. Reconstructed tomograms from unprocessed original projection images, however, are invariably affected by tomographic noise such as blurred images of objects lying outside the plane of interest and superimposed on the focused image of the fulcrum plane. The present work investigates the performance of two approaches for generation of tomograms with a reduced noise: a generalised post-processing method, based on constructing a noise mask from all planes in the reconstructed volume, and its subsequent subtraction from the in-focus plane and a filtered Multiple Projection Algorithm. The comparison between the two algorithms shows that the first method provides reconstructions with very good quality in case of high contrast features, especially for those embedded into a heterogeneous background.