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As these model parameters were inadequate to predict the residual α-amylase activity of BAA under dynamic conditions correctly, parameters were determined under dynamic conditions and subsequently successfully validated on an independent dynamic data set.
Segmentation was performed using KF applied to the dynamic data set and a source-to-background corrected 50% threshold (A50%) was applied to the sum image of the last three frames (45- to 60-min p.i .. Furthermore, several adaptations of KF were tested.
When should the dynamic data set be constructed and how it will be updated, if at all?
Therefore, the PET data were processed in two different ways according to the individual approach established in centre A and centre B. For centre A, the dynamic data set was framed into time intervals of 6 × 10 s, 4 × 30 s, 1 × 2 min, 3 × 5 min and 2 × 10 min and the data were reconstructed by filtered back projection (FBP) using a 5-mm Hann filter.
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We then proceed to study dynamic data sets, the analysis of which lead to a focus on insertion algorithms.
for the simultaneous display of a large number of dynamic data sets. of the output from this model.
Two of the dynamic data sets are used for model validation and the results shows adequate agreement between model and pilot plant data.
This includes steady state data for eight different conditions along with six dynamic data sets with relevant step changes in lean solvent flow rate and reboiler duty.
The model ensemble was identified using 14 different steady-state and dynamic data sets taken from literature.
Based on dynamic data sets, parametric imaging can be applied using different algorithms.
Following acquisition of five dynamic data sets, Gd-DTPA solution (0.01 ml g−1 body weight) was manually injected over 3 s into the tail vein of the animals.
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