
pmid: 16953039
This paper presents a mammography simulator and demonstrates its applicability in feasibility studies in dual-energy (DE) subtraction mammography. This mammography simulator is an evolution of a previously presented x-ray imaging simulation system, which has been extended with new functionalities that are specific for DE simulations. The new features include incident exposure and dose calculations, the implementation of a DE subtraction algorithm as well as amendments to the detector and source modelling. The system was then verified by simulating experiments and comparing their results against published data. The simulator was used to carry out a feasibility study of the applicability of DE techniques in mammography, and more precisely to examine whether this modality could result in better visualization and detection of microcalcifications. Investigations were carried out using a 3D breast software phantom of average thickness, monoenergetic and polyenergetic beam spectra and various detector configurations. Dual-shot techniques were simulated. Results showed the advantage of using monoenergetic in comparison with polyenergetic beams. Optimization studies with monochromatic sources were carried out to obtain the optimal low and high incident energies, based on the assessment of the figure of merit of the simulated microcalcifications in the subtracted images. The results of the simulation study with the optimal energies demonstrated that the use of the DE technique can improve visualization and increase detectability, allowing identification of microcalcifications of sizes as small as 200 microm. The quantitative results are also verified by means of a visual inspection of the synthetic images.
Phantoms, Imaging, Calcinosis, Reproducibility of Results, Breast Neoplasms, Models, Biological, Sensitivity and Specificity, Breast Diseases, Imaging, Three-Dimensional, Subtraction Technique, Humans, Computer Simulation, Female, Algorithms, Mammography
Phantoms, Imaging, Calcinosis, Reproducibility of Results, Breast Neoplasms, Models, Biological, Sensitivity and Specificity, Breast Diseases, Imaging, Three-Dimensional, Subtraction Technique, Humans, Computer Simulation, Female, Algorithms, Mammography
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