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Proceedings Paper

Application of the fractal Perlin noise algorithm for the generation of simulated breast tissue
Author(s): Magnus Dustler; Predrag Bakic; Hannie Petersson; Pontus Timberg; Anders Tingberg; Sophia Zackrisson
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Paper Abstract

Software breast phantoms are increasingly seeing use in preclinical validation of breast image acquisition systems and image analysis methods. Phantom realism has been proven sufficient for numerous specific validation tasks. A challenge is the generation of suitably realistic small-scale breast structures that could further improve the quality of phantom images. Power law noise follows the noise power characteristics of breast tissue, but may not sufficiently represent certain (e.g., non-Gaussian) properties seen in clinical breast images. The purpose of this work was to investigate the utility of fractal Perlin noise in generating more realistic breast tissue through investigation of its power spectrum and visual characteristics. Perlin noise is an algorithm that creates smoothly varying random structures of an arbitrary frequency. Through the use of a technique known as fractal noise or fractional Brownian motion (fBm), octaves of noise with different frequency are combined to generate coherent noise with a broad frequency range. fBm is controlled by two parameters – lacunarity and persistence – related to the frequency and amplitude of successive octaves, respectively. Average noise power spectra were calculated and beta parameters estimated in sample volumes of fractal Perlin noise with different combinations of lacunarity and persistence. Certain combinations of parameters resulted in noise volumes with beta values between 2 and 3, corresponding to reported measurements in real breast tissue. Different combinations of parameters resulted in different visual appearances. In conclusion, Perlin noise offers a flexible tool for generating breast tissue with realistic properties.

Paper Details

Date Published: 18 March 2015
PDF: 9 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123E (18 March 2015); doi: 10.1117/12.2081856
Show Author Affiliations
Magnus Dustler, Lund Univ. (Sweden)
Predrag Bakic, Univ. of Pennsylvania (United States)
Hannie Petersson, Lund Univ. (Sweden)
Pontus Timberg, Lund Univ. (Sweden)
Anders Tingberg, Lund Univ. (Sweden)
Sophia Zackrisson, Lund Univ. (Sweden)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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