Application of the fractal Perlin noise algorithm for the generation of simulated breast tissue

Magnus Dustler; Predrag Bakic; Hannie Petersson; Pontus Timberg; Anders Tingberg; Sophia Zackrisson

doi:10.1117/12.2081856

18 March 2015 Application of the fractal Perlin noise algorithm for the generation of simulated breast tissue

Magnus Dustler, Predrag Bakic, Hannie Petersson, Pontus Timberg, Anders Tingberg, Sophia Zackrisson

Proceedings Volume 9412, Medical Imaging 2015: Physics of Medical Imaging; 94123E (2015) https://doi.org/10.1117/12.2081856
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

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.

Citation Download Citation

Magnus Dustler, Predrag Bakic, Hannie Petersson, Pontus Timberg, Anders Tingberg, and Sophia Zackrisson "Application of the fractal Perlin noise algorithm for the generation of simulated breast tissue", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123E (18 March 2015); https://doi.org/10.1117/12.2081856

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available