Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitio...
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from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2jCvX3K via IFTTT
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Treatment effectiveness holds considerable importance in the association between service quality and satisfaction in medical service studies...
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Vol.25 No.2 from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/1P7bHxT via IFTTT
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Publication date: Available online 16 January 2017 Source: International Journal of Pediatric Otorhinolaryngology Author(s): Kaveh Karimn...
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Daily Mail Sarah was diagnosed with the cancer that killed Steve Jobs Daily Mail The symptoms Sarah Smith experienced on and off for...
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Omalizumab is a treatment for asthma that has a success rate of approximately 40% to 50%.1 Recent mechanistic studies have suggested that ba...
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Understanding Head And Neck Cancers - The Southeast Sun ... The Southeast Sun (NAPSI)—According to the Centers for Disease Control an...
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Abstract Background Henoch–Schönlein purpura is the most common vasculitis in children. Its long-term prognosis depends on renal involve...
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