Share Email Print

Proceedings Paper

Digital breast tomosynthesis reconstruction using spatially weighted non-convex regularization
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Regularization is an effective strategy for reducing noise in tomographic reconstruction. This paper proposes a spatially weighted non-convex (SWNC) regularization method for digital breast tomosynthesis (DBT) image reconstruction. With a non-convex cost function, this method can suppress noise without blurring microcalcifications (MC) and spiculations of masses. To minimize the non-convex cost function, we apply a majorize-minimize separable quadratic surrogate algorithm (MM-SQS) that is further accelerated by ordered subsets (OS). We applied the new method to a heterogeneous breast phantom and to human subject DBT data, and observed improved image quality in both situations. A quantitative study also showed that the SWNC method can significantly enhance the contrast-to-noise ratio of MCs. By properly selecting its parameters, the SWNC regularizer can preserve the appearance of the mass margins and breast parenchyma.

Paper Details

Date Published: 31 March 2016
PDF: 7 pages
Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 978369 (31 March 2016); doi: 10.1117/12.2216414
Show Author Affiliations
Jiabei Zheng, Univ. of Michigan (United States)
Jeffrey A. Fessler, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)

Published in SPIE Proceedings Vol. 9783:
Medical Imaging 2016: Physics of Medical Imaging
Despina Kontos; Thomas G. Flohr, Editor(s)

© SPIE. Terms of Use
Back to Top