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Proceedings Paper

Optimized lesion detection in digital breast tomosynthesis
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Paper Abstract

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.

Paper Details

Date Published: 13 March 2009
PDF: 9 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72580P (13 March 2009); doi: 10.1117/12.813964
Show Author Affiliations
Amarpreet S. Chawla, Duke Univ. (United States)
Ehsan Samei, Duke Univ. (United States)
Joseph Y. Lo, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)

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