The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Portrait of Predrag Bakic. Photo

Predrag Bakic

Associate Professor

Portrait of Predrag Bakic. Photo

Evaluation of non-Gaussian statistical properties in virtual breast phantoms

Author

  • Craig K. Abbey
  • Predrag R. Bakic
  • David D. Pokrajac
  • Andrew D.A. Maidment
  • Miguel P. Eckstein
  • John M. Boone

Summary, in English

Images derived from a "virtual phantom" can be useful in characterizing the performance of imaging systems. This has driven the development of virtual breast phantoms implemented in simulation environments. In breast imaging, several such phantoms have been proposed. We analyze the non-Gaussian statistical properties from three classes of virtual breast phantoms and compare them to similar statistics from a database of breast images. These include clustered-blob lumpy backgrounds (CBLBs), truncated binary textures, and the UPenn virtual breast phantoms. We use Laplacian fractional entropy (LFE) as a measure of the non-Gaussian statistical properties of each simulation procedure. Our results show that, despite similar power spectra, the simulation approaches differ considerably in LFE with very low scores for the CBLB to high values for the UPenn phantom at certain frequencies. These results suggest that LFE may have value in developing and tuning virtual phantom simulation procedures.

Publishing year

2019-04-01

Language

English

Publication/Series

Journal of Medical Imaging

Volume

6

Issue

2

Document type

Journal article

Publisher

SPIE

Keywords

  • breast phantoms
  • image statistics
  • Laplacian fractional entropy
  • natural scene statistics

Status

Published

ISBN/ISSN/Other

  • ISSN: 2329-4302