Title: Tomosynthesis reconstruction using an accelerated expectation maximisation algorithm with novel data structure based on sparse matrix ray-tracing method

Authors: Weihua Zhou, Apuroop Balla, Ying Chen

Addresses: Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901, USA. ' Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901, USA. ' Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901, USA

Abstract: Digital Breast Tomosynthesis (DBT) is a novel imaging technology to improve early breast cancer detection. It provides three-dimensional information of the breast to overcome the critical issues of overlapping anatomical structures of the breast. Among current available DBT reconstruction algorithms, Maximum Likelihood Expectation-Maximisation (MLEM) is a time-consuming iterative method to reconstruct three-dimensional image of the breast. In this paper, we proposed an accelerated MLEM algorithm with novel data structure based on sparse matrix ray-tracing method for DBT reconstruction. Compared with the standard MLEM, the proposed algorithm is effective to generate relative fast-speed tomosynthesis reconstruction and maintain the same image quality.

Keywords: mammography; tomosynthesis reconstruction; MLEM; maximum likelihood expectation maximisation; ray tracing; sparse matrix; impulse response; digital breast tomosynthesis; DBT; imaging technology; early detection; breast cancer; overlapping anatomical structures; cancer detection.

DOI: 10.1504/IJFIPM.2008.022152

International Journal of Functional Informatics and Personalised Medicine, 2008 Vol.1 No.4, pp.355 - 365

Published online: 21 Dec 2008 *

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