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Proceedings Paper

Construction of realistic liver phantoms from patient images using 3D printer and its application in CT image quality assessment
Author(s): Shuai Leng; Lifeng Yu; Thomas Vrieze; Joel Kuhlmann; Baiyu Chen; Cynthia H. McCollough
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Paper Abstract

The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered back-projection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered back-projection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.

Paper Details

Date Published: 18 March 2015
PDF: 7 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94124E (18 March 2015); doi: 10.1117/12.2082121
Show Author Affiliations
Shuai Leng, Mayo Clinic (United States)
Lifeng Yu, Mayo Clinic (United States)
Thomas Vrieze, Mayo Clinic (United States)
Joel Kuhlmann, Mayo Clinic (United States)
Baiyu Chen, Mayo Clinic (United States)
Cynthia H. McCollough, Mayo Clinic (United States)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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