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F J Beekman

Publications and source records attributed to F J Beekman.

14 recordsLinked to original sources
PubMed2001

Choice of collimator for cardiac SPET when resolution compensation is included in iterative reconstruction.

In clinical cardiac single-photon emission tomography (SPET) studies, collimators of different spatial resolution and geometric efficiency are available for imaging. In selecting the appropriate collimator for clinical use, there is a trade-off between spatial resolution, which can limit the contrast of the reconstructed image, and detection efficiency, which determines the noise in the image. Our objective was to assess which collimator is best suited for cardiac SPET when reconstruction is performed with and without compensation for distance-dependent resolution (CDR). The dynamic MCAT thorax phantom was used to simulate 180 degree technetium-99m cardiac data, acquired using either a general-purpose (GP) or high-resolution (HR) collimator. For GP and HR, the resolution at 15 cm was 11.5 mm and 9.5 mm respectively, and the corresponding relative efficiency was 1.0 and 0.52 respectively. Distance-dependent resolution, attenuation and noise were included in the projection data; scatter was not included. Ordered subsets expectation maximisation reconstruction (subset size 4) was performed with and without CDR. Results were evaluated by comparing the myocardial recovery coefficient and contrast between myocardium and ventricle relative to the original phantom, each plotted for different noise levels corresponding to increasing iteration number. The study demonstrated that, without CDR, HR gave the best results. However, for any given noise level with CDR, GP gave superior recovery and contrast. These findings were confirmed in a physical phantom study. Results suggest that improved reconstruction can be achieved using a GP collimator in combination with resolution compensation.

Algorithms↗
PubMed1999

Maximum likelihood estimation of cerebral blood flow in dynamic susceptibility contrast MRI.

For quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI), knowledge of the tissue response function is necessary. To obtain this, the tissue contrast passage measurement must be corrected for the arterial input. This study proposes an iterative maximum likelihood expectation maximization (ML-EM) algorithm for this correction, which takes into account the noise in T2- or T2*-weighted image sequences. The ML-EM algorithm does not assume a priori knowledge of the shape of the response function; it automatically corrects for arrival time offsets and inherently yields positive response values. The results on synthetic image sequences are presented, for which the recovered flow values and the response functions are in good agreement with their expectation values. The method is illustrated by calculating the gray and white matter flow in a clinical example.

Cerebrovascular Circulation↗
PubMed1999

The influence of backscatter material on 99mTc and 201Tl line source responses.

SPECT projections are contaminated by scatter, resulting in reduced image contrast and quantitative errors. When tissue is present behind the source, some of the detected photons backscatter via this tissue. Particularly in dual-isotope SPECT and in combined emission-transmission SPECT, backscatter constitutes a major part of the down-scatter contamination in lower-energy windows. In this paper, the effects of backscatter material were investigated. Planar images of 99mTc and 201Tl line sources between varying numbers of Perspex slabs were analysed using the photopeak windows and various scatter windows. In the 99mTc photopeak window no significant change in total counts due to backscatter material was measured. In the 201Tl photopeak window an increase of about 10% in total counts was observed. In the scatter windows an even more explicit influence of backscatter material was measured. For instance, at a forward depth of 10 cm, total counts of a 99mTc source detected in the 72 keV window eventually doubled with increasing backscatter material, compared with the situation without backscatter material. The backscatter contribution plateaued when more than 5-10 cm of scatter material was placed behind the source. In conclusion, backscatter should be taken into account, particularly in model-based down-scatter correction methods in dual-isotope SPECT and combined emission-transmission SPECT.

Gadolinium↗
PubMed1999

Efficient SPECT scatter calculation in non-uniform media using correlated Monte Carlo simulation.

Accurate simulation of scatter in projection data of single photon emission computed tomography (SPECT) is computationally extremely demanding for activity distribution in non-uniform dense media. This paper suggests how the computation time and memory requirements can be significantly reduced. First the scatter projection of a uniform dense object (P(SDSE)) is calculated using a previously developed accurate and fast method which includes all orders of scatter (slab-derived scatter estimation), and then P(SDSE) is transformed towards the desired projection P which is based on the non-uniform object. The transform of P(SDSE) is based on two first-order Compton scatter Monte Carlo (MC) simulated projections. One is based on the uniform object (P(u)) and the other on the object with non-uniformities (P(nu)). P is estimated by P = P(SDSE) P(nu)/P(u). A tremendous decrease in noise in P is achieved by tracking photon paths for P(nu) identical to those which were tracked for the calculation of P(u) and by using analytical rather than stochastic modelling of the collimator. The method was validated by comparing the results with standard MC-simulated scatter projections (P) of 99mTc and 201Tl point sources in a digital thorax phantom. After correction, excellent agreement was obtained between P and P. The total computation time required to calculate an accurate scatter projection of an extended distribution in a thorax phantom on a PC is a only few tens of seconds per projection, which makes the method attractive for application in accurate scatter correction in clinical SPECT. Furthermore, the method removes the need of excessive computer memory involved with previously proposed 3D model-based scatter correction methods.

Computer Simulation↗
PubMed1999

Estimation of the depth-dependent component of the point spread function of SPECT.

The point spread function (PSF) of a gamma camera describes the photon count density distribution at the detector surface when a point source is imaged. Knowledge of the PSF is important for computer simulation and accurate image reconstruction of single photon emission computed tomography (SPECT) images. To reduce the number of measurements required for PSF characterization and the amount of computer memory to store PSF tables, and to enable generalization of the PSF to different collimator-to-source distances, the PSF may be modeled as the two-dimensional (2D) convolution of the depth-dependent component which is free of detector blurring (PSF(ideal)) and the distance-dependent detector response. Owing to limitations imposed by the radioactive strength of point sources, extended sources have to be used for measurements. Therefore, if PSF(ideal) is estimated from measured responses, corrections have to be made for both the detector blurring and for the extent of the source. In this paper, an approach based on maximum likelihood expectation-maximization (ML-EM) is used to estimate PSF(ideal). In addition, a practical measurement procedure which avoids problems associated with commonly used line-source measurements is proposed. To decrease noise and to prevent nonphysical solutions, shape constraints are applied during the estimation of PSF(ideal). The estimates are generalized to depths other than those which have been measured and are incorporated in a SPECT simulator. The method is validated for Tc-99m and T1-201 by means of measurements on physical phantoms. The corrected responses have the desired shapes and simulated responses closely resemble measured responses. The proposed methodology may, consequently, serve as a basis for accurate three-dimensional (3D) SPECT reconstruction.

Algorithms↗
PubMed1998

Dual matrix ordered subsets reconstruction for accelerated 3D scatter compensation in single-photon emission tomography.

Three-dimensional (3D) iterative maximum likelihood expectation maximization (ML-EM) algorithms for single-photon emission tomography (SPET) are capable of correcting image-degrading effects of non-uniform attenuation, distance-dependent camera response and patient shape-dependent scatter. However, the resulting improvements in quantitation, resolution and signal-to-noise ratio (SNR) are obtained at the cost of a huge computational burden. This paper presents a new acceleration method for ML-EM: dual matrix ordered subsets (DM-OS). DM-OS combines two acceleration methods: (a) different matrices for projection and back-projection and (b) ordered subsets of projections. DM-OS was compared with ML-EM on simulated data and on physical thorax phantom data, for both 180 degrees and 360 degrees orbits. Contrast, normalized standard deviation and mean squared error were calculated for the digital phantom experiment. DM-OS resulted in similar image quality to ML-EM, even for speed-up factors of 200 compared to ML-EM in the case of 120 projections. The thorax phantom data could be reconstructed 50 times faster (60 projections) using DM-OS with preservation of image quality. ML-EM and DM-OS with scatter compensation showed significant improvement of SNR compared to ML-EM without scatter compensation. Furthermore, inclusion of complex image formation models in the computer code is simplified in the case of DM-OS. It is thus shown that DM-OS is a fast and relatively simple algorithm for 3D iterative scatter compensation, with similar results to conventional ML-EM, for both 180 degrees and 360 degrees acquired data.

Algorithms↗
PubMed1998

Selection of task-dependent diffusion filters for the post-processing of SPECT images.

Iterative reconstruction from single photon emission computed tomography (SPECT) data requires regularization to avoid noise amplification and edge artefacts in the reconstructed image. This is often accomplished by stopping the iteration process at a relatively low number of iterations or by post-filtering the reconstructed image. The aim of this paper is to develop a method to automatically select an optimal combination of stopping iteration number and filters for a particular imaging situation. To this end different error measures between the distribution of a phantom and a corresponding filtered SPECT image are minimized for different iteration numbers. As a study example, simulated data representing a brain study are used. For post-reconstruction filtering, the performance of 3D linear diffusion (Gaussian filtering) and edge preserving 3D nonlinear diffusion (Catté scheme) is investigated. For reconstruction methods which model the image formation process accurately, error measures between the phantom and the filtered reconstruction are significantly reduced by performing a high number of iterations followed by optimal filtering compared with stopping the iterative process early. Furthermore, this error reduction can be obtained over a wide range of iteration numbers. Only a negligibly small additional reduction of the errors is obtained by including spatial variance in the filter kernel. Compared with Gaussian filtering, Catté diffusion can further reduce the error in some cases. For the examples considered, using accurate image formation models during iterative reconstruction is far more important than the choice of the filter.

Biophysical Phenomena↗
PubMed1998

Accelerated iterative transmission CT reconstruction using an ordered subsets convex algorithm.

Iterative maximum likelihood (ML) transmission computed tomography algorithms have distinct advantages over Fourier-based reconstruction, but unfortunately require increased computation time. The convex algorithm [1] is a relatively fast iterative ML algorithm but it is nevertheless too slow for many applications. Therefore, an acceleration of this algorithm by using ordered subsets of projections is proposed [ordered subsets convex algorithm (OSC)]. OSC applies the convex algorithm sequentially to subsets of projections. OSC was compared with the convex algorithm using simulated and physical thorax phantom data. Reconstructions were performed for OSC using eight and 16 subsets (eight and four projections/subset, respectively). Global errors, image noise, contrast recovery, and likelihood increase were calculated. Results show that OSC is faster than the convex algorithm, the amount of acceleration being approximately proportional to the number of subsets in OSC, and it causes only a slight increase of noise and global errors in the reconstructions. Images and image profiles of the reconstructions were in good agreement. In conclusion, OSC and the convex algorithm result in similar image quality but OSC is more than an order of magnitude faster.

Algorithms↗
PubMed1998

Half-fanbeam collimators combined with scanning point sources for simultaneous emission-transmission imaging.

UNLABELLED: One type of SPECT system often used for simultaneous emission-transmission tomography is equipped with parallel-hole collimators, moving line sources (MLS) and electronic windows that move in synchrony with the sources. Although downscatter from the emission distribution is reduced by the use of the electronic window, this still can represent a sizable fraction of the transmitted counts. These systems have relatively poor spatial resolution and use costly transmission sources. METHODS: Using a two-head SPECT system, with heads at right angles, two 153Gd line sources (5800 MBq each) were replaced by two 153Gd point sources of only 750 MBq each and positioned to move along the focal lines of two half-fanbeam collimators. A suitable acquisition protocol for a moving point source (MPS) system was selected by considering the results of a simulation study. With this protocol, physical phantom experiments were conducted. RESULTS: Simulations showed that by using two half-fanbeam collimators, a gantry rotation of 90 degrees, such as used for 180 degrees acquisition with parallel-beam collimators for cardiac imaging, was insufficient. A gantry rotation of 180 degrees resulted in attenuation maps where only an area to the posterior of a 400-mm wide thorax phantom was affected by truncation. The MPS system had a 14.7 times higher sensitivity for transmission counts than the MLS system. Despite the smaller sources in the MPS system, the number of acquired transmission counts was a factor 1.91 times higher compared with the MLS system, resulting in reduced noise. The relative downscatter contribution from 99mTc (140 keV) in the 153Gd moving electronic window (100 keV) was reduced by a factor of 1.81. Transmission images of a rod phantom with segments containing acrylic rods of different diameters showed an improvement of resolution in favor of the MPS system from about 11 mm to about 6 mm (five instead of two segments of rods were clearly visible). In addition, the noise level in the MPS thorax transmission images was significantly lower. CONCLUSION: The MPS system has important advantages when compared with the MLS system. The use of low-activity point sources is economically beneficial when compared with line sources and reduces radiation exposure to staff and patients.

Equipment Design↗
PubMed1997

A clinical perspective of accelerated statistical reconstruction.

Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine.

Algorithms↗
PubMed1997

SPECT scatter modelling in non-uniform attenuating objects.

SPECT quantitation and image contrast are degraded by photon scatter. Water equivalent depths (WEDs) have been used by several investigators to model scatter responses in non-uniform attenuators. The drawback of this approach is the occurrence of undesired fluctuations in the shape of the scatter responses, as is shown by measurements. An improvement of the WED method is presented, based on the assumption that only a part of the scattering object (the region in the 'scatter cone') contributes significantly to the detected scatter events. The remaining part of the object is treated as a uniform medium. The extension of the WED method with extra-conical invariance (WEDECI) is evaluated by projection measurements of a phantom with a 99mTc source. Shapes of scatter responses predicted by the WEDECI method are found to agree better with the measurements than those predicted by conventional WEDs.

Algorithms↗
PubMed1997

Scatter compensation methods in 3D iterative SPECT reconstruction: a simulation study.

Effects of different scatter compensation methods incorporated in fully 3D iterative reconstruction are investigated. The methods are: (i) the inclusion of an 'ideal scatter estimate' (ISE); (ii) like (i) but with a noiseless scatter estimate (ISE-NF); (iii) incorporation of scatter in the point spread function during iterative reconstruction ('ideal scatter model', ISM); (iv) no scatter compensation (NSC); (v) ideal scatter rejection (ISR), as can be approximated by using a camera with a perfect energy resolution. The iterative method used was an ordered subset expectation maximization (OS-EM) algorithm. A cylinder containing small cold spheres was used to calculate contrast-to-noise curves. For a brain study, global errors between reconstruction and 'true' distributions were calculated. Results show that ISR is superior to all other methods. In all cases considered, ISM is superior to ISE and performs approximately as well as (brain study) or better than (cylinder data) ISE-NF. Both ISM and ISE improve contrast-to-noise curves and reduce global errors, compared with NSC. In the case of ISE, blurring of the scatter estimate with a Gaussian kernel results in slightly reduced errors in brain studies, especially at low count levels. The optimal Gaussian kernel size is strongly dependent on the noise level.

Algorithms↗
PubMedDate not supplied

Improvement of image resolution and quantitative accuracy in clinical Single Photon Emission Computed Tomography.

Clinical Single Photon Emission Computed Tomography (SPECT) is a scanning technique which acquires gamma-camera images ('projections') over a range of angles around a patient. These projections allow the reconstruction of cross sectional ('tomographic') images of the gamma-radiating pharmaceutical distribution in the patient, thus providing interesting information about the functioning of organs and tissues.SPECT images are seriously affected by a variety of image degrading processes. Restrictions on the amount of radio-pharmaceutical that can be administered to a patient cause noise in the projections and the limited spatial resolution of the gamma-camera results in blurring of the projections. In addition to these image degradations, the reconstruction of cross-sections is complicated by Compton scattering of gamma-photons in tissue, which causes attenuation of the photon flux received by the gamma-camera and causes improper detection of photons which have been scattered in tissue. This results in some additional blurring and loss of accuracy of the SPECT images in predicting activity concentrations. Tremendous efforts have been made to improve the quantitative accuracy and the spatial resolution of SPECT, and to reduce the noise in the reconstructed images. These efforts have resulted in corrective reconstruction algorithms, which are generally based on incorporation of accurate models of the main image degrading factors. Improvements of the data acquisition hardware can further increase image quality. In this paper, the image formation process of SPECT, including image-degrading factors, is explained. In addition, reconstruction algorithms and hardware modifications are reviewed, and their effects on image quality are illustrated with physical phantom and simulation experiments.

Algorithms↗