Automated Generation of Simulated 3D Breast Phantoms

The system automatically generates simulated 3D breast phantoms through computational geometry algorithms that model anatomical structures including lesions, ducts, fibroglandular tissue, and fatty tissue. The phantom generation employs stochastic modeling techniques with customizable parameters for tissue distribution and morphological characteristics. These phantoms serve as valuable resources for various breast phantom-based image analysis applications, including projection image simulation, CT reconstruction algorithm testing, and imaging system validation. Furthermore, the technology enables performance evaluation of breast tumor detection algorithms, facilitates research on breast disease development and progression, and supports testing of breast medical devices. Through continuous refinement and optimization of the phantom generation algorithms - potentially incorporating machine learning-based tissue modeling - this approach can enhance research accuracy and diagnostic capabilities in medical imaging, ultimately contributing to improved breast health assessment and treatment methodologies.