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Durham, NC 27710
These tools have a wide variety of applications in many different imaging modalities to investigate the effects of anatomical, physiological, physical, and instrumentational factors on medical imaging and to research new image acquisition strategies, image processing and reconstruction methods, and image visualization and interpretation techniques. We are currently applying them to the field of x-ray CT. The motivation for this work is the lack of sufficiently rigorous methods for optimizing the image quality and radiation dose in x-ray CT to the clinical needs of a given procedure. The danger of unnecessary radiation exposure from CT applications, especially for pediatrics, is just now being addressed. Optimization is essential in order for new and emerging CT applications to be truly useful and not represent a danger to the patient. Given the relatively high radiation doses required of current CT systems, thorough optimization is unlikely to ever be done in live patients. It would be prohibitively expensive to fabricate physical phantoms to simulate a realistic range of patient sizes and clinical needs especially when physiologic motion needs to be considered. The only practical approach to the optimization problem is through the use of realistic computer simulation tools developed in our work.
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Jadick, Giavanna, et al. “A scanner-specific framework for simulating CT images with tube current modulation.” Phys Med Biol, vol. 66, no. 18, Sept. 2021. Pubmed, doi:10.1088/1361-6560/ac2269.
Ria, Francesco, et al. “Comparison of 12 surrogates to characterize CT radiation risk across a clinical population.” Eur Radiol, vol. 31, no. 9, Sept. 2021, pp. 7022–30. Pubmed, doi:10.1007/s00330-021-07753-9.
Fu, Wanyi, et al. “iPhantom: A Framework for Automated Creation of Individualized Computational Phantoms and Its Application to CT Organ Dosimetry.” Ieee J Biomed Health Inform, vol. 25, no. 8, Aug. 2021, pp. 3061–72. Pubmed, doi:10.1109/JBHI.2021.3063080.