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Proceedings Paper

Synthetic CT: simulating arbitrary low dose single and dual energy protocols
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Paper Abstract

CT protocol selection (kVp, mAs, filtration) can greatly affect the dose delivered to a patient and the quality of the resulting images. While it is imperative to get diagnostic quality images from a study, the dose to the patient should be minimized. With synthetic CT, protocol optimization is made simple by simulating realistic scans of arbitrary low dose protocols from a previously acquired dual energy scan. For single energy protocols, the simulated projections have the same statistical properties as projections from an actual scan. The reconstruction of these synthesized projections then provides realistic images at a different protocol. For dual energy protocols, the material decomposition of the simulated protocol is directly synthesized. Moreover, the dose distribution from an arbitrary protocol (single or dual energy) can be found and used in conjunction with the predicted image quality for protocol design. We demonstrate single energy synthetic CT on a clinical study by synthesizing a 120 kVp image from a dual energy dataset. The synthesized image is compared to an actual 120 kVp image on the same patient, showing excellent agreement. We also describe a framework for implementing synthetic CT in software that is intuitive to use and allows radiologists to see the impact of protocol selection on image quality and dose distribution. A simple GUI demonstrates the vision for synthetic CT by allowing for the comparison of several dose reduction techniques: filtration, mA modulation, partial scan, or shielding. In particular, objects such as a breast shield can be simulated and virtually inserted as part of the original scan. In each case, the kVp and mAs can be adjusted while the synthesized image and dose profile are updated in real-time. With such software, synthetic CT can be applied as an educational and scientific tool for radiologists concerned with dose and image quality.

Paper Details

Date Published: 16 March 2011
PDF: 10 pages
Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79611R (16 March 2011); doi: 10.1117/12.878771
Show Author Affiliations
Adam S. Wang, Stanford Univ. (United States)
Norbert J. Pelc, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 7961:
Medical Imaging 2011: Physics of Medical Imaging
Norbert J. Pelc; Ehsan Samei; Robert M. Nishikawa, Editor(s)

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