TY - GEN
T1 - Noise reduction for cone-beam SPECT by penalized reweighted least-squares projection restoration
AU - Zhang, Hao
AU - Wen, Junhai
AU - Shi, Donghao
AU - Yang, Rui
AU - Wang, Jing
AU - Liang, Zhengrong
PY - 2013
Y1 - 2013
N2 - In single photon emission computed tomography(SPECT), the non-stationary Poisson noise in the projection data is one of the major degrading factors that jeopardize the quality of reconstructed images. In our previous researches for low-dose CT reconstruction, based on the noise properties of the log-transformed projection data, a penalized weighted least-squares (PWLS) cost function was constructed and the ideal projection data(i.e., line integral) was then estimated by minimizing the PWLS cost function. The experimental results showed the method could effectively suppress the noise without noticeable sacrifice of the spatial resolution for both fan- and cone-beam low-dose CT reconstruction. In this work, we tried to extend the PWLS projection restoration method to SPECT by redefining the weight term in PWLS cost function, because the weight is proportional to measured photon counts for transmission tomography(i.e., CT) while inversely proportional to measured photon counts for emission tomography (i.e., SPECT and PET). The iterative Gauss-Seidel algorithm was then used to minimize the cost function, and since the weight term was updated in each iteration, we refer our implementation as penalized reweighted least-squares (PRWLS) approach. The restorated projection data was then reconstructed by an analytical cone-beam SPECT reconstruction algorithm with compensation for non-uniform attenuation. Both high and low level Poisson noise was simulated in the cone-beam SPECT projection data, and the reconstruction results showed feasibility and efficacy of our proposed method on SPECT.
AB - In single photon emission computed tomography(SPECT), the non-stationary Poisson noise in the projection data is one of the major degrading factors that jeopardize the quality of reconstructed images. In our previous researches for low-dose CT reconstruction, based on the noise properties of the log-transformed projection data, a penalized weighted least-squares (PWLS) cost function was constructed and the ideal projection data(i.e., line integral) was then estimated by minimizing the PWLS cost function. The experimental results showed the method could effectively suppress the noise without noticeable sacrifice of the spatial resolution for both fan- and cone-beam low-dose CT reconstruction. In this work, we tried to extend the PWLS projection restoration method to SPECT by redefining the weight term in PWLS cost function, because the weight is proportional to measured photon counts for transmission tomography(i.e., CT) while inversely proportional to measured photon counts for emission tomography (i.e., SPECT and PET). The iterative Gauss-Seidel algorithm was then used to minimize the cost function, and since the weight term was updated in each iteration, we refer our implementation as penalized reweighted least-squares (PRWLS) approach. The restorated projection data was then reconstructed by an analytical cone-beam SPECT reconstruction algorithm with compensation for non-uniform attenuation. Both high and low level Poisson noise was simulated in the cone-beam SPECT projection data, and the reconstruction results showed feasibility and efficacy of our proposed method on SPECT.
KW - Noise reduction
KW - Non-uniform attenuation
KW - Penalized weighted least-squares
KW - Poisson noise
KW - SPECT reconstruction
UR - http://www.scopus.com/inward/record.url?scp=84878294161&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84878294161&partnerID=8YFLogxK
U2 - 10.1117/12.2007745
DO - 10.1117/12.2007745
M3 - Conference contribution
AN - SCOPUS:84878294161
SN - 9780819494429
T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
BT - Medical Imaging 2013
T2 - Medical Imaging 2013: Physics of Medical Imaging
Y2 - 11 February 2013 through 14 February 2013
ER -