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9 March 2017Computer simulation of low-dose CT with clinical lung image database: a preliminary study
Large samples of raw low-dose CT (LDCT) projections on lungs are needed for evaluating or designing novel and
effective reconstruction algorithms suitable for lung LDCT imaging. However, there exists radiation risk when getting
them from clinical CT scanning. To avoid the problem, a new strategy for producing large samples of lung LDCT
projections with computer simulations is proposed in this paper. In the simulation, clinical images from the publicly
available medical image database-the Lung Image Database Consortium(LIDC) and Image Database Resource Initiative
(IDRI) database (LIDC/IDRI) are used as the projected object to form the noise-free sinogram. Then by adding a Poisson
distributed quantum noise plus Gaussian distributed electronic noise to the projected transmission data calculated from
the noise-free sinogram, different noise levels of LDCT projections are obtained. At last the LDCT projections are used
for evaluating two reconstruction strategies. One is the conventional filtered back projection (FBP) algorithm and the
other is FBP reconstruction from the filtered sinogram with penalized weighted least square criterion (PWLS-FBP).
Images reconstructed with the LDCT simulations have shown that the PWLS-FBP algorithm performs better than the
FBP algorithm in reducing streaking artifacts and preserving resolution. Preliminary results indicate that the feasibility of
the proposed lung LDCT simulation strategy for helping to determine advanced reconstruction algorithms.
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Junyan Rong, Peng Gao, Wenlei Liu, Yuanke Zhang, Tianshuai Liu, Hongbing Lu, "Computer simulation of low-dose CT with clinical lung image database: a preliminary study," Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101322U (9 March 2017); https://doi.org/10.1117/12.2253973