While patient-based breast phantoms are realistic, they are limited by low resolution due to the image acquisition and segmentation process. The purpose of this study is to restore the high frequency components for the patient-based phantoms by adding power law noise (PLN) and breast structures generated based on mathematical models. First, 3D radial symmetric PLN with β=3 was added at the boundary between adipose and glandular tissue to connect broken tissue and create a high frequency contour of the glandular tissue. Next, selected high-frequency features from the FDA rule-based computational phantom (Cooper’s ligaments, ductal network, and blood vessels) were fused into the phantom. The effects of enhancement in this study were demonstrated by 2D mammography projections and digital breast tomosynthesis (DBT) reconstruction volumes. The addition of PLN and rule-based models leads to a continuous decrease in β. The new β is 2.76, which is similar to what typically found for reconstructed DBT volumes. The new combined breast phantoms retain the realism from segmentation and gain higher resolution after restoration.
Xinyuan Chen, Xiaolin Gong, Christian G. Graff, Maira Santana, Gregory M. Sturgeon, Thomas J. Sauer, Rongping Zeng, Stephen J. Glick, and Joseph Y. Lo, "High-resolution, anthropomorphic, computational breast phantom: fusion of rule-based structures with patient-based anatomy," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101321W (Presented at SPIE Medical Imaging: February 16, 2017; Published: 9 March 2017); https://doi.org/10.1117/12.2255913.
Conference Presentations are recordings of oral presentations given at SPIE conferences and published as part of the conference proceedings. They include the speaker's narration along with a video recording of the presentation slides and animations. Many conference presentations also include full-text papers. Search and browse our growing collection of more than 14,000 conference presentations, including many plenary and keynote presentations.