
Proceedings Paper
The development of a population of 4D pediatric XCAT phantoms for CT imaging research and optimizationFormat | Member Price | Non-Member Price |
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Paper Abstract
With the increased use of CT examinations, the associated radiation dose has become a large concern, especially for pediatrics. Much research has focused on reducing radiation dose through new scanning and reconstruction methods. Computational phantoms provide an effective and efficient means for evaluating image quality, patient-specific dose, and organ-specific dose in CT. We previously developed a set of highly-detailed 4D reference pediatric XCAT phantoms at ages of newborn, 1, 5, 10, and 15 years with organ and tissues masses matched to ICRP Publication 89 values. We now extend this reference set to a series of 64 pediatric phantoms of a variety of ages and height and weight percentiles, representative of the public at large. High resolution PET-CT data was reviewed by a practicing experienced radiologist for anatomic regularity and was then segmented with manual and semi-automatic methods to form a target model. A Multi-Channel Large Deformation Diffeomorphic Metric Mapping (MC-LDDMM) algorithm was used to calculate the transform from the best age matching pediatric reference phantom to the patient target. The transform was used to complete the target, filling in the non-segmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. 3D CT data was simulated from the phantoms to demonstrate their ability to generate realistic, patient quality imaging data. The population of pediatric phantoms developed in this work provides a vital tool to investigate dose reduction techniques in 3D and 4D pediatric CT.
Paper Details
Date Published: 19 March 2014
PDF: 4 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90331V (19 March 2014); doi: 10.1117/12.2043777
Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)
PDF: 4 pages
Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90331V (19 March 2014); doi: 10.1117/12.2043777
Show Author Affiliations
Hannah Norris, Duke Univ. (United States)
Yakun Zhang, Duke Univ. (United States)
Jack Frush, Duke Univ. (United States)
Gregory M. Sturgeon, Duke Univ. (United States)
Anum Minhas M.D., Duke Univ. (United States)
Daniel J. Tward, The Johns Hopkins Univ. (United States)
Yakun Zhang, Duke Univ. (United States)
Jack Frush, Duke Univ. (United States)
Gregory M. Sturgeon, Duke Univ. (United States)
Anum Minhas M.D., Duke Univ. (United States)
Daniel J. Tward, The Johns Hopkins Univ. (United States)
J. Tilak Ratnanather, The Johns Hopkins Univ. (United States)
M. I. Miller, The Johns Hopkins Univ. (United States)
Donald Frush M.D., Duke Univ. (United States)
Ehsan Samei, Duke Univ. (United States)
W. Paul Segars, Duke Univ. (United States)
M. I. Miller, The Johns Hopkins Univ. (United States)
Donald Frush M.D., Duke Univ. (United States)
Ehsan Samei, Duke Univ. (United States)
W. Paul Segars, Duke Univ. (United States)
Published in SPIE Proceedings Vol. 9033:
Medical Imaging 2014: Physics of Medical Imaging
Bruce R. Whiting; Christoph Hoeschen, Editor(s)
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