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Proceedings Paper

Truncation artifact and boundary artifact reduction in breast tomosynthesis reconstruction
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Paper Abstract

Digital Tomosynthesis Mammography (DTM) is an emerging technique that has the potential to improve breast cancer detection. DTM acquires low-dose mammograms at a number of projection angles over a limited angular range and reconstructs the 3D breast volume. Due to the limited number of projections within a limited angular range and the finite size of the detector, DTM reconstruction contains boundary and truncation artifacts that degrade the image quality of the tomosynthesized slices, especially that of the boundary and truncated regions. In this work, we developed artifact reduction methods that make use of both 2D and 3D breast boundary information and local intensity-equalization and tissue-compensation techniques. A breast phantom containing test objects and a selected DTM patient case were used to evaluate the effects of artifact reduction. The contrast-to-noise ratio (CNR), the normalized profiles of test objects, and a non-uniformity error index were used as performance measures. A GE prototype DTM system was used to acquire 21 PVs in 3° increments over a ±30° angular range. The Simultaneous Algebraic Reconstruction Technique (SART) was used for DTM reconstruction. Our results demonstrated that the proposed methods can improve the image quality both qualitatively and quantitatively, resulting in increased CNR value, background uniformity and an overall reconstruction quality comparable to that without truncation. For the selected DTM patient case, the obscured breast structural information near the truncated regions was essentially recovered. In addition, restricting SART reconstruction to be performed within the estimated 3D breast volume increased the computation efficiency.

Paper Details

Date Published: 18 March 2008
PDF: 9 pages
Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging, 69132Y (18 March 2008); doi: 10.1117/12.769698
Show Author Affiliations
Yiheng Zhang, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Yi-Ta Wu, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Chuan Zhou, Univ. of Michigan (United States)
Jun Wei, Univ. of Michigan (United States)
Jun Ge, Univ. of Michigan (United States)
Lubomir M. Hadjiiski, Univ. of Michigan (United States)
Jiazheng Shi, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 6913:
Medical Imaging 2008: Physics of Medical Imaging
Jiang Hsieh; Ehsan Samei, Editor(s)

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