Generation of 3D synthetic breast tissue

Premkumar Elangovan; David R. Dance; Kenneth C. Young; Kevin Wells

doi:10.1117/12.2216225

22 March 2016 Generation of 3D synthetic breast tissue

Premkumar Elangovan, David R. Dance, Kenneth C. Young, Kevin Wells

Proceedings Volume 9783, Medical Imaging 2016: Physics of Medical Imaging; 978308 (2016) https://doi.org/10.1117/12.2216225
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Virtual clinical trials are an emergent approach for the rapid evaluation and comparison of various breast imaging technologies and techniques using computer-based modeling tools. A fundamental requirement of this approach for mammography is the use of realistic looking breast anatomy in the studies to produce clinically relevant results. In this work, a biologically inspired approach has been used to simulate realistic synthetic breast phantom blocks for use in virtual clinical trials. A variety of high and low frequency features (including Cooper’s ligaments, blood vessels and glandular tissue) have been extracted from clinical digital breast tomosynthesis images and used to simulate synthetic breast blocks. The appearance of the phantom blocks was validated by presenting a selection of simulated 2D and DBT images interleaved with real images to a team of experienced readers for rating using an ROC paradigm. The average areas under the curve for 2D and DBT images were 0.53±.04 and 0.55±.07 respectively; errors are the standard errors of the mean. The values indicate that the observers had difficulty in differentiating the real images from simulated images. The statistical properties of simulated images of the phantom blocks were evaluated by means of power spectrum analysis. The power spectrum curves for real and simulated images closely match and overlap indicating good agreement.

Citation Download Citation

Premkumar Elangovan, David R. Dance, Kenneth C. Young, and Kevin Wells "Generation of 3D synthetic breast tissue", Proc. SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging, 978308 (22 March 2016); https://doi.org/10.1117/12.2216225

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