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While diagnostic improvement via breast tomosynthesis has been notable, the full potential of tomosynthesis
has not yet been realized. This is because of the complex task of optimizing multiple parameters that constitute
image acquisition and thus affect tomosynthesis performance. Those parameters include dose, number of
angular projections, and the total angular span of those projections. In this study, we investigated the effects of
acquisition parameters, independent of each other, on the overall diagnostic image quality of tomosynthesis.
Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of
each specimen were acquired at 6.2 times typical single-view mammographic dose level. Images at lower dose
levels were then simulated using a noise modification routine. Each projection image was supplemented with
84 simulated 3 mm 3D lesions embedded at the center of 84
non-overlapping ROIs. The projection images were
then reconstructed using a filtered-back projection (FBP) algorithm at 224 different combinations of acquisition
parameters to investigate which one of the many possible combinations maximized performance. Performance
was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion
detectability. Results showed that performance improved with an increase in the total acquisition dose level and
the angular span. At a constant dose level and angular span, the performance rolled-off beyond a certain number
of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily
improve its performance. The best performance was obtained with 15-17 projections spanning an angular arc of
~45° - the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The
optimization framework developed in this framework is applicable to other reconstruction techniques and other
multi-projection systems.
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