scholarly journals Spectral Analysis of Dynamic PET Studies

1993 ◽  
Vol 13 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Vincent J. Cunningham ◽  
Terry Jones
Keyword(s):  
Impulse Response ◽  
Time Course ◽  
Arterial Input Function ◽  
Impulse Response Function ◽  
Impulse Response Functions ◽  
Dynamic Pet ◽  
Computer Algorithms ◽  
Arterial Blood ◽  
Unit Impulse ◽  
Unit Impulse Response

We describe a new technique for the analysis of dynamic positron emission tomography (PET) studies in humans, where data consist of the time courses of label in tissue regions of interest and in arterial blood, following the administration of radiolabeled tracers. The technique produces a simple spectrum of the kinetic components which relate the tissue's response to the blood activity curve. From this summary of the kinetic components, the tissue's unit impulse response can be derived. The convolution of the arterial input function with the derived unit impulse response function gives the curve of best fit to the observed tissue data. The analysis makes no a priori assumptions regarding the number of compartments or components required to describe the time course of label in the tissue. Rather, it is based on a general linear model, presented here in a formulation compatible with its solution using standard computer algorithms. Its application is illustrated with reference to cerebral blood flow, glucose utilization, and ligand binding. The interpretation of the spectra, and of the tissue unit impulse response functions, are discussed in terms of vascular components, unidirectional clearance of tracer by the tissue, and reversible and irreversible phenomena. The significance of the number of components which can be identified within a given datum set is also discussed. The technique facilitates the interpretation of dynamic PET data and simplifies comparisons between regions and between subjects.

scholarly journals Convolution-based time-domain simulation for fluidelastic instability in tube arrays

2021 ◽  
Author(s):  
Mingjie Zhang ◽  
Ole Øiseth
Keyword(s):  
Impulse Response ◽  
Response Function ◽  
Time Domain ◽  
Impulse Response Function ◽  
Time Domain Simulation ◽  
Unit Step ◽  
Tube Arrays ◽  
Unit Impulse ◽  
The Time Domain ◽  
Unit Impulse Response

AbstractA convolution-based numerical algorithm is presented for the time-domain analysis of fluidelastic instability in tube arrays, emphasizing in detail some key numerical issues involved in the time-domain simulation. The unit-step and unit-impulse response functions, as two elementary building blocks for the time-domain analysis, are interpreted systematically. An amplitude-dependent unit-step or unit-impulse response function is introduced to capture the main features of the nonlinear fluidelastic (FE) forces. Connections of these elementary functions with conventional frequency-domain unsteady FE force coefficients are discussed to facilitate the identification of model parameters. Due to the lack of a reliable method to directly identify the unit-step or unit-impulse response function, the response function is indirectly identified based on the unsteady FE force coefficients. However, the transient feature captured by the indirectly identified response function may not be consistent with the physical fluid-memory effects. A recursive function is derived for FE force simulation to reduce the computational cost of the convolution operation. Numerical examples of two tube arrays, containing both a single flexible tube and multiple flexible tubes, are provided to validate the fidelity of the time-domain simulation. It is proven that the present time-domain simulation can achieve the same level of accuracy as the frequency-domain simulation based on the unsteady FE force coefficients. The convolution-based time-domain simulation can be used to more accurately evaluate the integrity of tube arrays by considering various nonlinear effects and non-uniform flow conditions. However, the indirectly identified unit-step or unit-impulse response function may fail to capture the underlying discontinuity in the stability curve due to the prespecified expression for fluid-memory effects.

Another Look at Z-transform Technique for Deriving Unit Impulse Response Function

2007 ◽  
Vol 21 (11) ◽  
pp. 1829-1848 ◽  
Author(s):  
R. K. Rai ◽  
M. K. Jain ◽  
S. K. Mishra ◽  
C. S. P. Ojha ◽  
V. P. Singh
Keyword(s):  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Unit Impulse ◽  
Unit Impulse Response

scholarly journals Gluconeogenesis from acetone in starved rats

1985 ◽  
Vol 231 (1) ◽  
pp. 151-155 ◽  
Author(s):  
G Hetenyi ◽  
C Ferrarotto
Keyword(s):  
Plasma Glucose ◽  
Time Course ◽  
Impulse Response Function ◽  
Metabolic Clearance ◽  
Plasma Lactate ◽  
Metabolic Clearance Rate ◽  
Unit Impulse ◽  
Anaesthetized Rats ◽  
Glucose Synthesis ◽  
Unit Impulse Response

To non-anaesthetized rats starved for 3 days, [U-14C]acetone, NaH14CO3, L-[U-14C]lactate, [2-14C]acetate or D-[U-14C]- plus D-[3-3H]-glucose was injected intravenously. From the change in the plasma concentration of labelled acetone versus time after the injection, the metabolic clearance rate of acetone was calculated as 2.25 ml/min per kg body wt., and its rate of turnover as 0.74 mumol/min per kg. The extent and time course of the labelling of plasma glucose, lactate, urea and acetoacetate were followed and compared with those observed after the injection of labelled lactate, acetate and NaHCO3. The labelling of plasma lactate was rapid and extensive. Some 1.37% of the 14C atoms of circulating glucose originated from plasma acetone, compared with 44% originating from lactate. By deconvolution of the Unit Impulse Response Function of glucose, it was shown that the flux of C atoms from acetone to glucose reached a peak at about 100 min after injection of labelled acetone. In comparable experiments the transfer from lactate reached a peak at 14 min after the injection of labelled lactate. It was concluded that acetone is converted into lactate to a degree sufficient to account for the labelling of plasma glucose and is thus a true, albeit minor, substrate of glucose synthesis in starved rats.

IMPROVING EXTRACTION OF IMPULSE RESPONSE FUNCTIONS USING STATIONARY WAVELET SHRINKAGE IN TERAHERTZ REFLECTION IMAGING

2010 ◽  
Vol 09 (04) ◽  
pp. 387-394 ◽  
Author(s):  
YANG CHEN ◽  
YIWEN SUN ◽  
EMMA PICKWELL-MACPHERSON
Keyword(s):  
Experimental Data ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Terahertz Imaging ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Inverse Filtering ◽  
Wavelet Shrinkage ◽  
Gaussian Filtering

In terahertz imaging, deconvolution is often performed to extract the impulse response function of the sample of interest. The inverse filtering process amplifies the noise and in this paper we investigate how we can suppress the noise without over-smoothing and losing useful information. We propose a robust deconvolution process utilizing stationary wavelet shrinkage theory which shows significant improvement over other popular methods such as double Gaussian filtering. We demonstrate the success of our approach on experimental data of water and isopropanol.

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