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Accurate determination of the input function is essential for absolute quantification of physiological parameters in positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging. Uncertainties associated with the input function due to such factors as measurement errors and inappropriate sampling protocols can hamper reliable estimation of physiological parameters. Although intravenous bolus injection has been a widely used tracer administration schedule, it imposes a sampling requirement around the peak of the blood curve where rapid blood sampling is needed to capture the dramatic changes of tracer kinetics. By administering tracer as a short-time constant infusion, such a sampling requirement can be relieved. Fitting an analytical function or a series of functions to the blood data is a common strategy to reduce statistical fluctuations. However, abrupt changes in the blood curve and differed in the injection schedule can cause ill-conditioned fitting. A physiological model that incorporated the injection schedule should be more appropriate for this task. The focus of this paper is to evaluate one such model for fitting blood data obtained with a short-time infusion of [18F]fluorodeoxyglucose (FDG). It was found that common analytical functions failed to fit the blood data in majority cases, whereas the physiological model that incorporated the injection schedule provided reliable and reproducible fits to the blood data.