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- W3015200293 abstract "Model based iterative reconstruction (MBIR) has attracted a lot of attention in X-ray computed tomography (CT). A strength of MBIR over classical filtered backprojection is its ability to apply constraints over the voxel values, which can be critical to improve image quality. Given that the linear attenuation coefficient of X-rays is non-negative, applying a non-negativity constraint appears very natural. Indeed, most MBIR-related publications in CT invoke it. However, there is little information in the literature on the intrinsic value of the non-negativity constraint. In this work, we investigate this question in the context of two challenging imaging scenarios: (i) heavy truncation, (ii) photon starvation due to a metal implant. Real CT data sets are used, and the effect of the constraint is examined in terms of closeness to a preferred ground truth. Additionally, convergence properties are studied. The reconstruction is performed using ordered subsets to obtain a result in a manner that can be practical for clinical routine applications. The experiments are an extension of a previous work where we extensively examined the effect of the non-negativity constraint. This was done using a provably converging reconstruction algorithm applied with a large number of iterations to nearly reach convergence. The results presented here are more nuanced than those observed in that examination. They show that, with ordered subsets, the nonnegativity constraint can be beneficial or detrimental depending on the imaging scenario. However, the observed differences tend to be much smaller than the overall level of inaccuracy in the image. We also find that the non-negativity constraint can prevent divergence when using ordered subsets, but this gain does not translate into a satisfactory reconstruction." @default.
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- W3015200293 date "2019-10-01" @default.
- W3015200293 modified "2023-10-16" @default.
- W3015200293 title "On the Value of the Non-negativity Constraint in CT" @default.
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- W3015200293 doi "https://doi.org/10.1109/nss/mic42101.2019.9059667" @default.
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