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Proceedings Paper

Lesion insertion in projection domain for computed tomography image quality assessment
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Paper Abstract

To perform task-based image quality assessment in CT, it is desirable to have a large number of realistic patient images with known diagnostic truth. One effective way to achieve this objective is to create hybrid images that combine patient images with simulated lesions. Because conventional hybrid images generated in the image-domain fails to reflect the impact of scan and reconstruction parameters on lesion appearance, this study explored a projection-domain approach. Liver lesion models were forward projected according to the geometry of a commercial CT scanner to acquire lesion projections. The lesion projections were then inserted into patient projections (decoded from commercial CT raw data with the assistance of the vendor) and reconstructed to acquire hybrid images. To validate the accuracy of the forward projection geometry, simulated images reconstructed from the forward projections of a digital ACR phantom were compared to physically acquired ACR phantom images. To validate the hybrid images, lesion models were inserted into patient images and visually assessed. Results showed that the simulated phantom images and the physically acquired phantom images had great similarity in terms of HU accuracy and high-contrast resolution. The lesions in the hybrid image had a realistic appearance and merged naturally into the liver background. In addition, the inserted lesion demonstrated reconstruction-parameter-dependent appearance. Compared to conventional image-domain approach, our method enables more realistic hybrid images for image quality assessment.

Paper Details

Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94121R (18 March 2015); doi: 10.1117/12.2082049
Show Author Affiliations
Baiyu Chen, Mayo Clinic (United States)
Chi Ma, Mayo Clinic (United States)
Zhicong Yu, Mayo Clinic (United States)
Shuai Leng, Mayo Clinic (United States)
Lifeng Yu, Mayo Clinic (United States)
Cynthia 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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