Title :
A Simple Low-Dose X-Ray CT Simulation From High-Dose Scan
Author :
Dong Zeng ; Jing Huang ; Zhaoying Bian ; Shanzhou Niu ; Hua Zhang ; Qianjin Feng ; Zhengrong Liang ; Jianhua Ma
Author_Institution :
Sch. of Biomed. Eng., Southern Med. Univ., Guangzhou, China
Abstract :
Low-dose X-ray computed tomography (CT) simulation from a high-dose scan is required in optimizing radiation dose to patients. In this paper, we propose a simple low-dose CT simulation strategy in the sinogram domain using the raw data from high-dose scan. Specially, a relationship between the incident fluxes of low- and high-dose scans is first determined according to the repeated projection measurements and analysis. Second, the incident flux level of the simulated low-dose scan is generated by properly scaling the incident flux level of the high-dose scan via the determined relationship in the first step. Third, the low-dose CT transmission data by energy integrating detection is simulated by adding a statistically independent Poisson noise distribution plus a statistically independent Gaussian noise distribution. Finally, a filtered back-projection (FBP) algorithm is implemented to reconstruct the resultant low-dose CT images. The present low-dose simulation strategy is verified on the simulations and real scans by comparing it with the existing low-dose CT simulation tool. Experimental results demonstrated that the present low-dose CT simulation strategy can generate accurate low-dose CT sinogram data from high-dose scans in terms of qualitative and quantitative measurements.
Keywords :
Gaussian distribution; Gaussian noise; Poisson distribution; computerised tomography; image filtering; image reconstruction; medical image processing; energy integrating detection; filtered back-projection algorithm; high-dose scan; incident flux level; low-dose CT image reconstruction; low-dose CT transmission data; low-dose X-ray CT simulation; low-dose X-ray computed tomography simulation; projection measurements; radiation dose; sinogram domain; statistically independent Gaussian noise distribution; statistically independent Poisson noise distribution; Computational modeling; Computed tomography; Data models; Detectors; Image reconstruction; Noise; Noise measurement; High-dose; X-ray computed tomography (CT); low-dose; simulation;
Journal_Title :
Nuclear Science, IEEE Transactions on
DOI :
10.1109/TNS.2015.2467219