Abstract
We are currently investigating the application of tomosynthesis to lung nodule detection using technology developed for the Scanning-Beam Digital X-ray (SBDX) system[1]. For system understanding and optimization, the interplay of various parameters must be investigated via simulations. We present a fast image-based SBDX system simulation model that produces equivalent tomosynthesis reconstructions to those from a physics-based model. Comparison between the two models were made using the central 75% of the reconstructed images. After applying geometric corrections arising from the SBDX system geometry, image-based model results were different by less than 3% and computed more than 10 times faster than physics-based model with comparable quality results. This work provides groundwork for SBDX system optimization for lung nodule detection. Furthermore, such analysis can be generalized to any tomosynthesis system for which the acquisition geometry is well known.
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