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Extraction of pencil beam kernels by the deconvolution method.

A method has been developed to extract pencil beam kernels from measured broad beam profiles. In theory, the convolution of a symmetric kernel with a step function will yield a function that is symmetric about the inflection point. Conversely, by deconvolution, the kernel may be extracted from a measured distribution. In practice, however, due to the uncertainties and errors associated with the measurements and due to the singularities produced in the fast Fourier transforms employed in the deconvolution process, the kernels thus obtained and the dose distributions calculated therefrom, often exhibit erratic fluctuations. We propose a method that transforms measured profiles to new, modified distributions so that they satisfy the theoretical symmetry condition. The resultant kernel from the deconvolution is then free of fluctuations. We applied this method to compute photon and electron dose distributions at various depths in water and electron fluence distributions in air. The agreement between measured and computed profiles is within 1% in dose or 1 mm in distance in high dose gradient regions.

Fourier Analysis↗

The use of deconvolution and total least squares in recovering a radiation detector line spread function.

We present a method for obtaining the line spread function (LSF) of any radiation detector from measured data. The problem of finding a LSF is essentially a discrete deconvolution from known values of the input (Monte Carlo generated data) and the output (measured data) which can be put into matrix form. We applied the total least squares (TLS) method which is particularly useful when there are errors in both the input and output data. Results from computer simulation as well as from actual data are shown. In a practical application, however, our technique is currently limited by the ability of the Monte Carlo data to simulate correctly the inherent data from the head of the linear accelerator (linac). To overcome this difficulty we have solved by deconvolution and TLS for a more realistic inherent beam profile of our linac using the information from both profile data as measured with film and the film densitometer response function. The LSF of the densitometer was estimated with a simple method of direct measurement of a slit image and a full width at half maximum (FWHM) of 0.997 mm was recorded. Additionally, using the knowledge of this realistic inherent profile of the linac, a blurring function representing the finite source size effect missing in our current Monte Carlo profile simulation was determined. Finally, with the realistic inherent beam profile we have applied the deconvolution and TLS method to find a LSF for the Markus chamber and found a resulting FWHM of 5.39 mm. The TLS approach for deconvolving can find a useful application for both finding the LSF and correcting for the detector size effect once its LSF is known. This type of correction is required when a high spatial resolution is needed (e.g., in small field off-axis measurements). Convolved and measured profiles are also presented to illustrate the effect of the blurring due to different LSFs.

Biophysical Phenomena↗

Minimum entropy deconvolution of pulse-echo signals acquired from attenuative layered media.

In this article deconvolution of ultrasonic pulse-echo data acquired from attenuative layered media is considered. The problem is divided in two subproblems: treating the sparse reflection sequence caused by the layered structure of the media and treating the frequency-dependent attenuation. The first subproblem is solved by means of joint maximum a posteriori estimation of the assumed zero mean, white, nonstationary reflection sequence and its corresponding sequence of unknown standard deviations. This approach leads to an algorithm that seeks minimum entropy solutions for the reflection sequence and therefore the algorithm serves as a novel link between the classical Wiener filter and methods for sparse or minimum entropy deconvolution. The second subproblem is solved by introducing a new signal processing-oriented, linear discrete-time model for frequency-dependent attenuation in isotropic and homogeneous media. The deconvolution algorithm is tested using simulated data and its performance for real normal incidence pulse-echo data from a composite material is also demonstrated. The results show that the algorithm, in combination with the attenuation model, yields estimates that reveal the internal structure of the composite and, thus, simplify the interpretation of the ultrasonic data.

Journal Article↗

CT perfusion scanning with deconvolution analysis: pilot study in patients with acute middle cerebral artery stroke.

PURPOSE: To measure mean cerebral blood flow (CBF) in ischemic and nonischemic territories and in low-attenuation regions in patients with acute stroke by using deconvolution-derived hemodynamic imaging. MATERIALS AND METHODS: Twelve patients with acute middle cerebral artery stroke and 12 control patients were examined by using single-section computed tomography (CT) perfusion scanning. Analysis was performed with a deconvolution-based algorithm. Comparisons of mean CBF, cerebral blood volume (CBV), and mean transit time (MTT) were determined between hemispheres in all patients and between low- and normal-attenuation regions in patients with acute stroke. Two independent readers examined the images for extent of visually apparent regional perfusion abnormalities. The data were compared with extent of final infarct in seven patients with acute stroke who underwent follow-up CT or magnetic resonance imaging. RESULTS: Significant decreases in CBF (-50%, P =.001) were found in the affected hemispheres of patients with acute stroke. Significant changes in CBV (-26%, P =.03) and MTT (+111%, P =.004) were also seen. Significant alterations in perfusion were also seen in low- compared with normal-attenuation areas. Pearson correlation between readers for extent of CBF abnormality was 0.94 (P =.001). Intraobserver variation was 8.9% for CBF abnormalities. CONCLUSION: Deconvolution analysis of CT perfusion data is a promising method for evaluation of cerebral hemodynamics in patients with acute stroke.

Adult↗

Reconstructing the rate of appearance of subcutaneous insulin by deconvolution.

In this paper a deconvolution scheme is presented to reconstruct the rate of appearance of subcutaneously injected insulin. Relevant aspects of experiment design are briefly described. Intravenous insulin kinetics are modeled to determine the impulse response of the system. The deconvolution problem is not ill conditioned and is solved using a least-squares method without imposing constraints on the input. An estimate of the error of the reconstructed input is provided. The reliability of the deconvolution scheme is tested by means of an independent validation study. Finally, the different sources of error that affect the method are discussed, and a figure of the global error is derived.

Humans↗

Hydrocortisone secretion: production rate and pulse characterization by numerical deconvolution.

Based on serial blood sampling over 24 h, hydrocortisone was shown to be secreted episodically in the horse. The purpose of the present experiment was to characterize peaks and troughs by analyzing the instantaneous secretion rate profile obtained by a deconvolution technique rather than from the plasma concentration time profile. Kinetic parameters of hydrocortisone were determined following intravenous bolus and intravenous perfusion of hydrocortisone. Stationary and nonlinearity of hydrocortisone disposition were demonstrated. With the use of clearance values calculated from constant perfusion administration, the 24-h hydrocortisone production rate was estimated at 0.46 +/- 0.08 mg.kg-1.24 h-1. The instantaneous secretory profile was reconstituted by deconvoluting the plasma concentration profile using structural parameters determined from the bolus hydrocortisone administration. When this secretory profile was subjected to a pulse analysis program, the number of detected peaks was found to be 17.25 +/- 1.26 and the mean peak duration 34.01 +/- 5.52 min. The total duration of secretory activity was estimated at 582.5 +/- 63.97 min. By comparison, when the plasma concentration profile was analyzed directly, the number of peaks was only 10.0 +/- 1.41 but their mean duration was much longer, i.e., 105.25 +/- 21.24 min. The origin of these differences and the advantages and limits of deconvolution analysis are discussed.

Animals↗

Impact of sampling technique on appraisal of pulsatile insulin secretion by deconvolution and cluster analysis.

Little is known about the optimal experimental conditions for assessing pulsatile insulin secretion in vivo. To address this, we employed a recently validated canine model (n = 12) to determine the consequences of 1) sampling from the systemic circulation (SC) vs. the portal vein (PV), 2) sampling intensity and duration, and 3) deconvolution vs. cluster analysis on assessing pulsatile insulin secretion. PV vs. SC sampling resulted in a approximately 40% higher pulse frequency by deconvolution (9.0 +/- 0.5 vs. 6.6 +/- 0.9 pulses/h, P < 0.02) and cluster analysis (7.5 +/- 0.3 vs. 5.6 +/- 0.6 pulses/h, P < 0.01) due to a higher signal-to-noise ratio (19 +/- 4.8 PV vs. 12 +/- 1.8 SC). PV sampling also disclosed a higher calculated contribution of the pulsatile vs. nonpulsatile mode of delivery to total insulin secretion (57 +/- 4 vs. 28 +/- 5%, P < 0.001). Analysis of the relevance of sampling intensity revealed that 1-min data yielded a markedly higher estimate of pulse frequency with PV sampling than 2-min data (9.0 +/- 0.5 vs. 5.4 +/- 0.5, P < 0.02, deconvolution; 7.5 +/- 0.3 vs. 4.3 +/- 0.6 pulses/h, P < 0.001, cluster). Optimal sampling duration was shown to be 40 min or more. We conclude that the resolving power of the analytical tool, the anatomic site of blood withdrawal, the frequency of blood sampling, and the duration of the total observation interval all significantly influence estimated insulin secretory pulse frequency and the fraction of insulin secreted in pulses. With the assumption that PV 1-min insulin data constitute the "gold standard," our in vivo inferences of 7.5-9.0 insulin pulses/h closely recapitulate in vitro islet secretory activity.

Animals↗

Glucose production during an IVGTT by deconvolution: validation with the tracer-to-tracee clamp technique.

Recently, a new method, based on a two-compartment minimal model and deconvolution [A. Caumo and C. Cobelli. Am. J. Physiol 264 (Endocrinol. Metab. 37): E829-E841, 1993; P. Vicini, G. Sparacino, A. Caumo, and C. Cobelli. Comput. Meth. Prog. Biomed. 52: 147-156, 1997], has been proposed to estimate endogenous glucose production (EGP) from labeled intravenous glucose tolerance test (IVGTT) data. Our aim here is to compare this EGP profile with that independently obtained with the reference method, based on the tracer-to-tracee ratio (TTR) clamp. An insulin-modified (0.03 U/kg body wt infused over 5 min) [6,6-2H2]glucose-labeled IVGTT (0.33 g/kg of glucose) was performed in 10 normal subjects. A second tracer ([U-13C]glucose) was also infused during the test in a variable fashion to clamp endogenous glucose TTR. The TTR clamp was quite successful. As a result, the EGP profile, reconstructed from [U-13C]glucose data with the models of Steele and Radziuk, were almost superimposable. The deconvolution-obtained EGP profile, calculated from [6,6-2H2]glucose data, showed remarkable agreement with that obtained from the TTR clamp. Some differences between the two profiles were noted in the estimated basal EGP and in the initial modalities of EGP inhibition. A high interindividual variability was also observed with both methods in the resumption of EGP to baseline; variability was high in both the timing and the extent of resumption. In conclusion, the use of the two-compartment minimal model of the IVGTT and deconvolution allows the estimation of a profile of EGP that is in very good agreement with that independently obtained with a TTR clamp.

Adult↗

Model-free numerical deconvolution of recirculating indicator concentration curves.

This paper investigates two model-free methods for numerical deconvolution of recirculating indicator concentration curves. The two methods, damped least squares and discrete orthogonal polynomial deconvolution, are applied to simulated data to verify the reliability of the algorithms. Both deconvolution methods provide damping that results in estimated transport functions that are smooth and reasonable estimates of the actual simulated transport function. On convolution with the simulated input curve, the estimated transport functions provide good fits to the simulated output curve. In addition, methods for identifying an optimal solution and for truncating the artifactually long oscillatory tails of the estimated transport functions are proposed, which appear to allow for reasonably accurate estimation of the mean transit times and variances of the transport functions as well. When either method was applied to indicator dilution data obtained from the pulmonary artery and left atrium, it was computationally stable while producing transport functions that when convolved with the input concentration curves provided good fits to the output concentration curves. The combined simulation and experimental results suggest that the proposed methods should be useful for estimating circulation transport functions from indicator dilution data.

Algorithms↗

Three-dimensional organization of microtubules in tumor cells studied by confocal laser scanning microscopy and computer-assisted deconvolution and image reconstruction.

Confocal microscopy, image deconvolution and computer-assisted methods have been used to reconstruct the three-dimensional (3-D) distribution of tubulin in cells. The techniques were applied to tumor cells growing under regular culture conditions (planar cultivation) and those penetrating into reconstituted collagen matrices (spatial cultivation). As expected the application of deconvolution algorithms enhanced the resolution of results. The deconvolution using the maximum likelihood estimation included the measurement of the point spread function of the optical setup. The data visualization of the resulting data sets uses volume as well as surface rendering approaches. The 3-D reconstruction gives a clear image of the spatial arrangement of tubulin fibers in relation to cell shape and position of other cellular organelles, particularly the nucleus. The tubulin forms an intricate network of fibers of variable thickness. The highest tubulin concentrations appear in the cell periphery and particularly in pseudopodia/invadopodia. This is indicative of an enhanced transport of intracellular material facilitating cell movement and lysis of the extracellular matrix. The investigation is assumed to stimulate further experiments using a variety of techniques leading to the complete understanding of the spatial architecture of living cells.

Cell Movement↗

Porcine and human insulin absorption from subcutaneous tissues in normal and insulin-dependent diabetic subjects: a deconvolution-based approach.

The mechanisms of sc insulin absorption are not understood, and models for interpreting in vivo data cannot be developed without gross simplification. To overcome this difficulty we developed a new approach which makes use of deconvolution analysis and does not require any model of the sc tissue. In five normal subjects and seven insulin-dependent diabetic (IDDM) patients endogenous insulin secretion was suppressed by means of a hypoglycemic glucose clamp procedure (approximately 2.8 mmol/L) sustained by a continuous insulin infusion (approximately 4 pmol/min.kg). A bolus injection of insulin (5.4 nmol) was administered iv, and plasma insulin concentrations were measured frequently for 2 h to assess iv insulin kinetics. Insulin then was injected sc in the abdominal region, and plasma insulin concentrations were measured for 8 h. Each subject was studied twice, with porcine and semisynthetic human insulin (Actrapid, Novo). The rate of insulin absorption was reconstructed by deconvolution from the plasma concentrations and iv insulin kinetic data. Linearity of the iv insulin kinetics, essential for deconvolution analysis, was confirmed by a dose-response study in the range of the measured concentrations (150-1800 pmol/L). In most instances, a two-compartment model was adequate to describe the iv response. The mean plasma insulin clearance rates were 15.5 +/- 1.9 (+/- SD) mL/min.kg (porcine) and 17.2 +/- 6.0 (human) in normal subjects and 20.7 +/- 8.8 (porcine) and 20.9 +/- 9.1 (human) in the IDDM patients. The rate of appearance of human insulin from sc tissue was faster than that of porcine insulin in both normal and IDDM subjects, but no significant differences were found in bioavailability, which was 55 +/- 12% (+/- SD; porcine) and 61 +/- 34% (human) in the normal subjects, and 84 +/- 28% (porcine) and 86 +/- 23% (human) in the IDDM patients. The rate of absorption and bioavailability were higher in the IDDM patients than in the normal subjects, a difference possibly related to increased sc blood flow in the IDDM patients. No differences were found with regard to glucose requirement values, normalized to plasma insulin concentrations, in agreement with the finding that the bioavailability of the two insulin species was similar.

Adolescent↗

Deconvolution of emission tomographic data: a clinical evaluation.

A method of improving the quality of images in single photon emission computed tomography (SPECT) is demonstrated using transaxial images of the liver and brain. Deconvolution of the nuclear medicine data by a point source response function (PSRF) acquired previously in a scattering medium attempts to compensate for scattered radiation within the patient. The average geometric response of the collimator of the gamma camera is also compensated for with this technique. Three patients with known metastatic lesions in the liver and three with primary lesions in the brain were imaged. Clinical assessment of reconstructed slices both before and after deconvolution demonstrates that compensating for the effects of scatter and of collimator blurring leads to enhanced detail of pathological lesions. In all cases, cold lesions seen prior to deconvolution were enhanced in detail and, in addition, new lesions were seen with this technique.

Adult↗

Calculation of the static in-flight telescope-detector response by deconvolution applied to point-spread function for the geostationary earth radiation budget experiment.

The Geostationary Earth Radiation Budget (GERB) experiment is a broadband satellite radiometer instrument program intended to resolve remaining uncertainties surrounding the effect of cloud radiative feedback on future climate change. By use of a custom-designed diffraction-aberration telescope model, the GERB detector spatial response is recovered by deconvolution applied to the ground calibration point-spread function (PSF) measurements. An ensemble of randomly generated white-noise test scenes, combined with the measured telescope transfer function results in the effect of noise on the deconvolution being significantly reduced. With the recovered detector response as a base, the same model is applied in construction of the predicted in-flight field-of-view response of each GERB pixel to both short- and long-wave Earth radiance. The results of this study can now be used to simulate and investigate the instantaneous sampling errors incurred by GERB. Also, the developed deconvolution method may be highly applicable in enhancing images or PSF data for any telescope system for which a wave-front error measurement is available.

Journal Article↗

Improved accuracy of reconstructed diffuse optical tomographic images by means of spatial deconvolution: two-dimensional quantitative characterization.

Systematic characterization studies are presented, relating to a previously reported spatial deconvolution operation that seeks to compensate for the information-blurring property of first-order perturbation algorithms for diffuse optical tomography (DOT) image reconstruction. In simulation results that are presented, this deconvolution operation has been applied to two-dimensional DOT images reconstructed by solving a first-order perturbation equation. Under study was the effect on algorithm performance of control parameters in the measurement (number and spatial distribution of sources and detectors, presence of noise, and presence of systematic error), target (medium shape; and number, location, size, and contrast of inclusions), and computational (number of finite-element-method mesh nodes, length of filter-generating linear system, among others) parameter spaces associated with computation and the use of the deconvolution operators. Substantial improvements in reconstructed image quality, in terms of recovered inclusion location, size, and contrast, are found in all cases. A finding of practical importance is that the method is robust to appreciable differences between the optical coefficients of the media used for filter generation and those of the target media to which the filters are subsequently applied.

Algorithms↗

4Pi microscopy deconvolution with a variable point-spread function.

To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.

Journal Article↗

Robust, noniterative, and computationally efficient modification of van Cittert deconvolution optical figuring.

A modification of van Cittert deconvolution (VCD) is introduced and shown to yield a robust, noniterative (or closed-form), and numerically efficient method of deconvolution. This modification removes the restrictions limiting the applicability of conventional VCD only to shapes and relative positions of the convolved functions for which it converges, while also avoiding the ill effects of zeros in these functions. The resulting method is computationally efficient because it is noniterative and uses the fast Fourier transform. In contrast to the convergences obtained with VCD, those obtained with this modified method are ensured by their expansion in terms of an introduced auxiliary function rather than the convolved functions. This permits both the general removal of the above limitations and arbitrarily accurate deconvolution of infinitely sampled input data even in the presence of input data noise. For discretely sampled input data the accuracy of this modification is shown to be limited only by the implicit bandwidth of the input data density. To exemplify its numerical and analytical advantages, I apply the method to computer control of optical surface figuring. I also demonstrate an intrinsic means of optimal frequency filtering of raw input data made available by this modification. The advantages of this procedure are also applicable to image restoration.

Computer Simulation↗

Iterative statistical approach to blind image deconvolution

Image deblurring has long been modeled as a deconvolution problem. In the literature, the point-spread function (PSF) is often assumed to be known exactly. However, in practical situations such as image acquisition in cameras, we may have incomplete knowledge of the PSF. This deblurring problem is referred to as blind deconvolution. We employ a statistical point of view of the data and use a modified maximum a posteriori approach to identify the most probable object and blur given the observed image. To facilitate computation we use an iterative method, which is an extension of the traditional expectation-maximization method, instead of direct optimization. We derive separate formulas for the updates of the estimates in each iteration to enhance the deconvolution results, which are based on the specific nature of our a priori knowledge available about the object and the blur.

Journal Article↗

Relative focus map estimation using blind deconvolution.

An automatic focus map extraction method is presented that uses a modification of blind deconvolution for estimation of localized blurring functions. We use these local blurring functions [so-called point-spread functions (PSFs)] for extraction of focus areas on ordinary images. In this inverse task our goal is not image reconstruction but the estimation of localized PSFs and the relative focus map. Thus the method is less sensitive than general deconvolution is to noise and ill-posed deconvolution problems. The focus areas can be estimated without any knowledge of the shooting conditions or of the optical system used.

Algorithms↗