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Proceedings Paper

Methodology of NEQ (f) analysis for optimization and comparison of digital breast tomosynthesis acquisition techniques and reconstruction algorithms
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Paper Abstract

As a new three-dimensional imaging technique, digital breast tomosynthesis allows the reconstruction of an arbitrary set of planes in the breast from a limited-angle series of projection images. Though several tomosynthesis algorithms have been proposed, no complete optimization and comparison of different tomosynthesis acquisition techniques for available methods has been conducted as of yet. This paper represents a methodology of noise-equivalent quanta NEQ (f) analysis to optimize and compare the efficacy of tomosynthesis algorithms and imaging acquisition techniques for digital breast tomosynthesis. It combines the modulation transfer function (MTF) of system signal performance and the noise power spectrum (NPS) of noise characteristics. It enables one to evaluate the performance of different acquisition parameters and algorithms for comparison and optimization purposes. An example of this methodology was evaluated on a selenium-based direct-conversion flat-panel Siemens Mammomat Novation prototype system. An edge method was used to measure the presampled MTF of the detector. The MTF associated with the reconstruction algorithm and specific acquisition technique was investigated by calculating the Fourier Transform of simulated impulse responses. Flat field tomosynthesis projection sequences were acquired and then reconstructed. A mean-subtracted NPS on the reconstructed plane was studied to remove fixed pattern noise. An example of the application of this methodology was illustrated in this paper using a point-by-point Back Projection correction (BP) reconstruction algorithm and an acquisition technique of 25 projections with 25 degrees total angular tube movement.

Paper Details

Date Published: 16 March 2007
PDF: 9 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65101I (16 March 2007); doi: 10.1117/12.713737
Show Author Affiliations
Ying Chen, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
Joseph Y. Lo, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
Nicole T. Ranger, Duke Univ. Medical Ctr. (United States)
Ehsan Samei, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
James T. Dobbins III, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)

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