Raped calculation of detectability in Bayesian SPECT
Tóm tắt
To speed up the laborious process of optimizing and comparing SPECT imaging systems, computational methods using model observers can be used to predict human performance in the context of a lesion detection task. We address the case of SPECT images reconstructed by Bayesian MAP methods and the use of a channelized Hotelling observer (CHO) for a detection task. It is possible to write a closed-form theoretical expression to evaluate an image quality figure-of-merit (FOM) for this case. The evaluation of this FOM expression is intractably computationally intensive due, it turns out, to the nature of attenuation and depth-dependent blur in SPECT. We make several approximations that make this computation tractable, and validate our new expressions using Monte-Carlo simulations.
Từ khóa
#Bayesian methods #Optimization methods #Computational modeling #Context modeling #Predictive models #Humans #Lesions #Image reconstruction #Image quality #AttenuationTài liệu tham khảo
qi, 1999, A Theoretical Study of the Contrast Recovery and Variance of MAP Reconstructions from PET Data, IEEE Trans Med Imag, 18
10.1109/83.491322
xing, 2001, Efficient Calculation of Resolution and Variance in 2D Circular-Orbit SPECT, Conf Rec IEEE Nuc Sci Sym Med lmag Conf
10.1109/83.535846
10.1109/42.938249
10.1109/42.370406
10.1364/JOSAA.4.002447
10.1109/23.873017
10.1073/pnas.90.21.9758