ArticleJournal of medical imaging (Bellingham, Wash.)2014
Region of interest based Hotelling observer for computed tomography with comparison to alternative methods.
Article in Journal of medical imaging (Bellingham, Wash.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Investigating simulation-based metrics for characterizing linear iterative reconstruction in digital breast tomosynthesis.Medical physics · 2017Article
- Use of the Hotelling observer to optimize image reconstruction in digital breast tomosynthesis.Journal of medical imaging (Bellingham, Wash.) · 2016Article
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3 authors.
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Abstract
We compare several approaches to estimation of Hotelling observer (HO) performance in x-ray computed tomography (CT). We consider the case where the signal of interest is small so that the reconstructed image can be restricted to a small region of interest (ROI) surrounding the signal. This reduces the dimensionality of the image covariance matrix so that direct computation of HO metrics within the ROI is feasible. We propose that this approach is directly applicable to systems optimization in CT; however, many alternative approaches exist, which make computation of HO performance tractable through a range of approximations, assumptions, or estimation strategies. Here, we compare several of these methods, including the use of Laguerre-Gauss channels, discrete Fourier domain computation of the HO (which assumes noise stationarity), and two approaches to HO estimation through samples of noisy images. Since our method computes HO performance exactly within an ROI, this allows us to investigate the validity of the assumptions inherent in various common approaches to HO estimation, such as the stationarity assumption in the case of the discrete Fourier transform domain method.
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