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Projection images from digital breast tomosynthesis acquisitions can contain a large fraction of scattered x-rays due to the absence of an anti-scatter grid in front of the detector. In order to produce quantitative results, this should be accounted for in reconstruction algorithms. We examine the possible improvement in signal difference to noise ratio (SDNR) for low contrast spherical densities when applying a scatter correction algorithm.
Hybrid patient data were created by combining real patient data with attenuation profiles of spherical masses acquired with matching exposure settings. Scatter in these cases was estimated using Monte-Carlo based scatter- ing kernels. All cases were reconstructed using filtered backprojection (FBP) with and without beam hardening correction and two maximum likelihood methods for transmission tomography, with and without quadratic smoothing prior (MAPTR and MLTR). For all methods, images were reconstructed without scatter correction, and with scatter precorrection, and for the iterative methods also with an adjusted update step obtained by including scatter in the physics model. SDNR of the inserted spheres was calculated by subtracting the recon- structions with and without inserted template to measure the signal difference, while noise was measured in the image containing the template.
SDNR was significantly improved by 3.5% to 4.5% (p < 0.0001) at iteration 10 for both correction methods applied to the MLTR and MAPTR reconstructions. For MLTR these differences disappeared by iteration 100. For regular FBP SDNR remained the same after correction (p = 0.60) while it dropped slightly for FBP with beam hardening correction (-1.4%, p = 0.028).
These results indicate that for the iterative methods, application of a scatter correction algorithm has very little effect on the SDNR, it only causes a slight decrease in convergence speed, which is similar for precorrection and correction incorporated in the update step. The FBP results were unchanged because the scatter being corrected is a low frequency component in the projection images, and this information is mostly ignored in the reconstruction due to the high pass filter.
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