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Portrait of Predrag Bakic. Photo

Predrag Bakic

Associate Professor

Portrait of Predrag Bakic. Photo

Evaluating the sensitivity of the optimization of acquisition geometry to the choice of reconstruction algorithm in digital breast tomosynthesis through a simulation study

Author

  • Rongping Zeng
  • Subok Park
  • Predrag Bakic
  • Kyle J. Myers

Summary, in English

Due to the limited number of views and limited angular span in digital breast tomosynthesis (DBT), the acquisition geometry design is an important factor that affects the image quality. Therefore, intensive studies have been conducted regarding the optimization of the acquisition geometry. However, different reconstruction algorithms were used in most of the reported studies. Because each type of reconstruction algorithm can provide images with its own image resolution, noise properties and artifact appearance, it is unclear whether the optimal geometries concluded for the DBT system in one study can be generalized to the DBT systems with a reconstruction algorithm different to the one applied in that study. Hence, we investigated the effect of the reconstruction algorithm on the optimization of acquisition geometry parameters through carefully designed simulation studies. Our results show that using various reconstruction algorithms, including the filtered back-projection, the simultaneous algebraic reconstruction technique, the maximum-likelihood method and the total-variation regularized least-square method, gave similar performance trends for the acquisition parameters for detecting lesions. The consistency of system ranking indicates that the choice of the reconstruction algorithm may not be critical for DBT system geometry optimization.

Publishing year

2015-02-07

Language

English

Pages

1259-1288

Publication/Series

Physics in Medicine and Biology

Volume

60

Issue

3

Document type

Journal article

Publisher

IOP Publishing

Topic

  • Medical Biotechnology

Keywords

  • channelized hotelling observer
  • digital breast tomosynthesis
  • image quality assessment
  • image reconstruction
  • lesion detectability
  • system optimization

Status

Published

ISBN/ISSN/Other

  • ISSN: 0031-9155