Reliable and efficient deconvolution technique based on total linear least squares for calculating the renal retention function

By deconvolving the activity/time curves obtained from the blood and kidney, the renal retention function can be calculated, yielding useful clinical data. However, the current deconvolution techniques are not very reliable; they are sensitive to the inaccuracies present in the data. A more reliable, stable and efficient deconvolution technique based on the singular value decomposition, total linear least squares (TLLS), is proposed and its properties are described. The applicability of TLLS as a deconvolution technique in renography is discussed and demonstrated. Results from simulation, as well as from clinical data, are presented to show the advantages of the use of TLLS with respect to noise rejection in the data. They confirm the superiority of TLLS over the current deconvolution techniques. It is concluded that TLLS needs no smoothing and is a powerful, efficient, reliable and stable deconvolution technique.

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