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Proceedings Paper

Limited data tomographic image reconstruction via dual formulation of total variation minimization
Author(s): Kwang Eun Jang; Younghun Sung; Kangeui Lee; Jongha Lee; Seungryong Cho
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Paper Abstract

The X-ray mammography is the primary imaging modality for breast cancer screening. For the dense breast, however, the mammogram is usually difficult to read due to tissue overlap problem caused by the superposition of normal tissues. The digital breast tomosynthesis (DBT) that measures several low dose projections over a limited angle range may be an alternative modality for breast imaging, since it allows the visualization of the cross-sectional information of breast. The DBT, however, may suffer from the aliasing artifact and the severe noise corruption. To overcome these problems, a total variation (TV) regularized statistical reconstruction algorithm is presented. Inspired by the dual formulation of TV minimization in denoising and deblurring problems, we derived a gradient-type algorithm based on statistical model of X-ray tomography. The objective function is comprised of a data fidelity term derived from the statistical model and a TV regularization term. The gradient of the objective function can be easily calculated using simple operations in terms of auxiliary variables. After a descending step, the data fidelity term is renewed in each iteration. Since the proposed algorithm can be implemented without sophisticated operations such as matrix inverse, it provides an efficient way to include the TV regularization in the statistical reconstruction method, which results in a fast and robust estimation for low dose projections over the limited angle range. Initial tests with an experimental DBT system confirmed our finding.

Paper Details

Date Published: 17 March 2011
PDF: 8 pages
Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 796138 (17 March 2011); doi: 10.1117/12.877832
Show Author Affiliations
Kwang Eun Jang, Samsung Advanced Institute of Technology (Korea, Republic of)
Younghun Sung, Samsung Advanced Institute of Technology (Korea, Republic of)
Kangeui Lee, Samsung Advanced Institute of Technology (Korea, Republic of)
Jongha Lee, Samsung Advanced Institute of Technology (Korea, Republic of)
Seungryong Cho, KAIST (Korea, Republic of)


Published in SPIE Proceedings Vol. 7961:
Medical Imaging 2011: Physics of Medical Imaging
Norbert J. Pelc; Ehsan Samei; Robert M. Nishikawa, Editor(s)

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