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A computational model to generate simulated three-dimensional breast masses.

Luis de Sisternes¹, Jovan G Brankov¹, Adam M Zysk¹

¹Medical Imaging Research Center, Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, Illinois 60616.

Medical Physics

|February 6, 2015

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Researchers developed algorithms to create realistic 3D simulated breast masses for mammograms. These simulated masses were indistinguishable from real ones by both computer-aided diagnosis and expert readers.

Area of Science:

Medical Imaging
Computational Biology
Radiology

Background:

Realistic simulation of breast masses is crucial for improving mammogram analysis and computer-aided diagnosis (CAD) systems.
Current methods may lack the fidelity required for robust evaluation of diagnostic tools.

Purpose of the Study:

To develop algorithms for generating high-resolution, realistic three-dimensional (3D) simulated breast masses with user-defined characteristics.
To embed these simulated masses into actual clinical mammograms to create hybrid images.
To evaluate the realism of these simulated masses using CAD systems and expert radiologist readers.

Main Methods:

Utilized a modified stochastic Gaussian random sphere model for the core mass and an iterative fractal branching algorithm for spicules.

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Embedded generated 3D masses into digitized mammograms.

Assessed realism by comparing CAD features and expert reader performance on real versus hybrid mammogram pairs.

Main Results:

No statistically significant differences were found in CAD features between real and simulated masses (spiculated or non-spiculated margins).
Expert radiologists demonstrated poor performance in distinguishing simulated masses within hybrid images from real mammograms.

Conclusions:

The developed method enables realistic simulation of 3D breast masses with controllable attributes for creating diverse hybrid mammograms.
The computational model is suitable for breast mass detectability studies, CAD algorithm evaluation, and educational purposes in radiology.