Non-Gaussian statistical properties of virtual breast phantoms

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


Images derived from a phantom are useful for characterizing the performance of imaging systems. In particular, the modulation transfer properties of imaging detectors are traditionally assessed by physical phantoms consisting of an edge. More recently researchers have come to realize that quantifying the effects of object variability can also be accomplished with phantoms in modalities such as breast imaging where anatomical structure may be the principal limitation in performance. This has driven development of virtual phantoms that can be used in simulation environments. In breast imaging, several such phantoms have been proposed. In this work, we analyze non-Gaussian statistical properties of virtual phantoms, and compare them to similar statistics from a database of breast images. The virtual phantoms assessed consist of three classes. The first is known as clustered-blob lumpy backgrounds. The second class is binarized textures which typically apply some sort of threshold to a stochastic 3D texture intended to represent the distribution of adipose and glandular tissue in the breast. The third approach comes from efforts at the University of Pennsylvania to directly simulate the 3D anatomy of the breast. We use Laplacian fractional entropy (LFE) as a measure of the non-Gaussian statistical properties of each simulation. Our results show that the simulation approaches differ considerably in LFE with very low scores for the clustered-blob lumpy background to very high values for the UPenn phantom. These results suggest that LFE may have value in developing and tuning virtual phantom simulation procedures.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISBN (Print)9780819498304
StatePublished - 2014
EventMedical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States
Duration: Feb 16 2014Feb 17 2014


OtherMedical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment
Country/TerritoryUnited States
CitySan Diego, CA


  • And natural scene statistics
  • Breast phantoms
  • Image statistics
  • Laplacian Fractional Entropy

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


Dive into the research topics of 'Non-Gaussian statistical properties of virtual breast phantoms'. Together they form a unique fingerprint.

Cite this