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Proceedings Paper

Low dose CT reconstruction with nonlocal means-based prior predicted from normal-dose CT database
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Paper Abstract

The penalized weighted least-squares (PWLS) image reconstruction with the widely used edge-preserving nonlocal means (NLM) penalty has shown the potential to significantly improve the image quality for low dose CT (LDCT). Considering the nonlocal weights have significant effects for the smoothness and resolution of the reconstruction, much effort has been made to improve their accuracy. A high quality image of normal dose with less noise and artifacts is sometimes used for the weight’s calculation to further improvement. However, registration should be employed first when misalignment between the low-dose and normal-dose scans cannot be ignored. It will bring an extra work and the effect of registration error on the proposed method are uncertain. The paper aims to propose a new NLM prior model based on normal-dose CT (NDCT) without registration, by predicting nonlocal weights with selecting most similar patch samples from FDCT database. The patch samples are determined by evaluating the similarity between patches from NDCT and the target patch of LDCT. After building up the normal dose based NLM penalty, the PWLS object function is iteratively minimized for reconstruction. Preliminary reconstruction with LDCT data has shown its potential in the structure detail preservation.

Paper Details

Date Published: 12 March 2018
PDF: 5 pages
Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057821 (12 March 2018); doi: 10.1117/12.2294051
Show Author Affiliations
Junyan Rong, Fourth Military Medical Univ. (China)
Yuanke Zhang, Fourth Military Medical Univ. (China)
Tianshuai Liu, Fourth Military Medical Univ. (China)
Peng Gao, Fourth Military Medical Univ. (China)
Yuxiang Xing, Tsinghua Univ. (China)
Zhengrong Liang, The State Univ. of New York at Stony Brook (United States)
Hongbing Lu, Fourth Military Medical Univ. (China)

Published in SPIE Proceedings Vol. 10578:
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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