Higher-order scene statistics of breast images

Craig K. Abbey; Jascha N. Sohl-Dickstein; Bruno A. Olshausen; Miguel P. Eckstein; John M. Boone

doi:10.1117/12.813797

12 March 2009 Higher-order scene statistics of breast images

Craig K. Abbey, Jascha N. Sohl-Dickstein, Bruno A. Olshausen, Miguel P. Eckstein, John M. Boone

Author Affiliations +

Proceedings Volume 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment; 726317 (2009) https://doi.org/10.1117/12.813797
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural scenes. It is argued that this allows for sparse representation of the independent components of natural images [Olshausen and Field, Nature, 1996]. These theories have important implications for medical image perception. For example, will a system that is designed to represent the independent components of natural scenes, where objects occlude one another and illumination is typically reflected, be appropriate for X-ray imaging, where features superimpose on one another and illumination is transmissive? In this research we begin to examine these issues by evaluating higher-order statistical properties of breast images from X-ray projection mammography (PM) and dedicated breast computed tomography (bCT). We evaluate kurtosis in responses of octave bandwidth Gabor filters applied to PM and to coronal slices of bCT scans. We find that kurtosis in PM rises and quickly saturates for filter center frequencies with an average value above 0.95. By contrast, kurtosis in bCT peaks near 0.20 cyc/mm with kurtosis of approximately 2. Our findings suggest that the human visual system may be tuned to represent breast tissue more effectively in bCT over a specific range of spatial frequencies.

Citation Download Citation

Craig K. Abbey, Jascha N. Sohl-Dickstein, Bruno A. Olshausen, Miguel P. Eckstein, and John M. Boone "Higher-order scene statistics of breast images", Proc. SPIE 7263, Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment, 726317 (12 March 2009); https://doi.org/10.1117/12.813797

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