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

8 Citations (Scopus)

Abstract

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
PublisherSPIE
Volume9037
ISBN (Print)9780819498304
DOIs
StatePublished - 2014
EventMedical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment - San Diego, CA, United States
Duration: Feb 16 2014Feb 17 2014

Other

OtherMedical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment
CountryUnited States
CitySan Diego, CA
Period2/16/142/17/14

Fingerprint

breast
Breast
Entropy
Imaging techniques
Textures
entropy
Imaging systems
textures
adipose tissues
environment simulation
Tuning
Modulation
Statistics
Tissue
simulation
anatomy
Detectors
Adipose Tissue
Anatomy
tuning

Keywords

  • 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

Cite this

Abbey, C. K., Bakic, P. R., Pokrajac, D. D., Maidment, A. D. A., Eckstein, M. P., & Boone, J. M. (2014). Non-Gaussian statistical properties of virtual breast phantoms. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE (Vol. 9037). [90370G] SPIE. https://doi.org/10.1117/12.2044446

Non-Gaussian statistical properties of virtual breast phantoms. / Abbey, Craig K.; Bakic, Predrag R.; Pokrajac, David D.; Maidment, Andrew D A; Eckstein, Miguel P.; Boone, John M.

Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9037 SPIE, 2014. 90370G.

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

Abbey, CK, Bakic, PR, Pokrajac, DD, Maidment, ADA, Eckstein, MP & Boone, JM 2014, Non-Gaussian statistical properties of virtual breast phantoms. in Progress in Biomedical Optics and Imaging - Proceedings of SPIE. vol. 9037, 90370G, SPIE, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, San Diego, CA, United States, 2/16/14. https://doi.org/10.1117/12.2044446
Abbey CK, Bakic PR, Pokrajac DD, Maidment ADA, Eckstein MP, Boone JM. Non-Gaussian statistical properties of virtual breast phantoms. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9037. SPIE. 2014. 90370G https://doi.org/10.1117/12.2044446
Abbey, Craig K. ; Bakic, Predrag R. ; Pokrajac, David D. ; Maidment, Andrew D A ; Eckstein, Miguel P. ; Boone, John M. / Non-Gaussian statistical properties of virtual breast phantoms. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 9037 SPIE, 2014.
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