Preconstruction restoration of myocardial single photon emission computed tomography images

A restoration scheme for single photon emission computed tomography (SPECT) images that performs restoration before reconstruction (preconstruction restoration) from planar (projection) images is presented. A comparison is performed between results obtained in this study and those obtained by a method reported previously where the restoration is performed after reconstruction (postreconstruction restoration). The filters investigated are the Wiener and power spectrum equalization filters. These filters are applied to SPECT images of a hollow cylinder phantom and a cardiac phantom acquired on a Siemens Rota camera. Quantitative analyses of the results are performed through measurements of contrast ratios and root mean squared errors. The preconstruction restored images show a significant decrease in the root mean squared error and an increase in contrast over the postconstruction restored images.     

A prototype rotating slat collimator for single photon emission computed tomography

A collimator consisting of a series of highly attenuating parallel slats has been constructed and used in conjunction with a gamma-camera to approximately measure planar projections of a given radionuclide distribution. The enlarged solid angle of acceptance afforded by the slat collimator gave rise to an increased geometric efficiency of between 12 and 28 times that observed with a low-energy high-resolution (LEHR) parallel-hole collimator. When the slats rotated over the face of the detector and the camera gantry turned about the object, sufficient projections were acquired to reconstruct a three-dimensional (3-D) image using the inversion of the 3-D radon transform. The noise behavior of an algorithm for implementing this inversion was studied analytically and the resulting relationship has been verified by computer simulation. The substantially improved geometric efficiency of the slat collimator translated to improvements in reconstructed signal-to-noise ratio (SNR) by, at best, up to a factor of 2.0 with respect to standard parallel-hole collimation. The spatial resolution achieved with the slat collimator was comparable to that obtained with a LEHR collimator and no significant differences were observed in terms of scatter response. Accurate image quantification was hindered by the spatially variant response of the slat collimator.     

A pixel-based approach for classification of cardiac single photon emission computed tomography images

In this work, a computer-based algorithm is proposed for the initial interpretation of human cardiac images. Reconstructed single photon emission computed tomography images are used to differentiate between subjects with normal value and abnormal value of ejection fraction. The method analyses pixel intensities that correspond to blood flow in the left ventricular region. The algorithm proceeds through three main stages: the initial stage does a pre-processing task to reduce noise as well as blur in the image. The second stage extracts features from the images. Classification is done in the final stage. The pre-processing stage consists of a de-noising part and a de-blurring part. Novel features are used for classification. Features are extracted as three different sets based on: the pixel intensity distribution in different regions, spatial relationship of pixels and multi-scale image information. Two supervised algorithms are proposed for classification: one algorithm is based on a threshold value computed from the features extracted from the training images and the other algorithm is based on sequential minimal optimization-based support vector machine approach. Experimental studies were performed on real cardiac SPECT images obtained from hospital. The result of classification has been verified by an expert nuclear medicine physician and by the ejection fraction value obtained from quantitative gated SPECT, the most widely used software package for quantifying gated SPECT images.     

Two-dimensional restoration of single photon emission computed tomography images using the Kalman filter

The discrete filtered backprojection (DFBP) algorithm used for the reconstruction of single photon emission computed tomography (SPECT) images affects image quality because of the operations of filtering and discretization. The discretization of the filtered backprojection process can cause the modulation transfer function (MTF) of the SPECT imaging system to be anisotropic and nonstationary, especially near the edges of the camera's field of view. The use of shift-invariant restoration techniques fails to restore large images because these techniques do not account for such variations in the MTF. This study presents the application of a two-dimensional (2D) shift-variant Kalman filter for post-reconstruction restoration of SPECT slices. This filter was applied to SPECT images of a hollow cylinder phantom; a resolution phantom; and a large, truncated cone phantom containing two types of cold spots, a sphere, and a triangular prism. The images were acquired on an ADAC GENESYS camera. A comparison was performed between results obtained by the Kalman filter and those obtained by shift-invariant filters. Quantitative analysis of the restored images performed through measurement of root mean squared errors shows a considerable reduction in error of Kalman-filtered images over images restored using shift-invariant methods.     

A cone-beam filtered backprojection reconstruction algorithm for cardiac single photon emission computed tomography

A filtered backprojection reconstruction algorithm was developed for cardiac single photon emission computed tomography with cone-beam geometry. The algorithm reconstructs cone-beam projections collected from ;short scan' acquisitions of a detector traversing a noncircular planar orbit. Since the algorithm does not correct for photon attenuation, it is designed to reconstruct data collected over an angular range of slightly more than 180 degrees with the assumption that the range of angles is oriented so as not to acquire the highly attenuated posterior projections of emissions from cardiac radiopharmaceuticals. This sampling scheme is performed to minimize the attenuation artifacts that result from reconstructing posterior projections. From computer simulations, it is found that reconstruction of attenuated projections has a greater effect upon quantitation and image quality than any potential cone-beam reconstruction artifacts resulting from insufficient sampling of cone-beam projections. With nonattenuated projection data, cone beam reconstruction errors in the heart are shown to be small (errors of at most 2%).     

3-D maximum a posteriori estimation for single photon emission computed tomography on massively-parallel computers

A fully three-dimensional (3-D) implementation of the maximum a posteriori (MAP) method for single photon emission computed tomography (SPECT) is demonstrated. The 3-D reconstruction exhibits a major increase in resolution when compared to the generation of the series of separate 2-D slice reconstructions. As has been noted, the iterative EM algorithm for 2-D reconstruction is highly computational; the 3-D algorithm is far worse. To accommodate the computational complexity, previous work in the 2-D arena is extended, and an implementation on the class of massively parallel processors of the 3-D algorithm is demonstrated. Using a 16000- (4000-) processor MasPar/DECmpp-Sx machine, the algorithm is demonstrated to execute at 2.5 (7.8) s/EM-iteration for the entire 64x64x64 cube of 96 planar measurements obtained from the Siemens Orbiter rotating camera operating in the high-resolution mode.     

Single-photon emission computed tomography

The subject of singl-photon emission computed tomography (SPECT) is generally reviewed. The basic interaction processes of gamma rays in matter are outlined, and the formation of conventional gamma-ray images is described. We then outline the extension of these concepts to the formation of three-dimensional or tomographic images. Of particular concern in emission tomography, the effects of gamma-ray attenuation and scattering are outlined. Several examples are given of practical SPECT systems, and representative results are given.     

Simulated annealing image reconstruction method for a pinhole aperture single photon emission computed tomograph (SPECT)

A series of computer experiments was performed to determine the relative performance of simulated annealing, quenched annealing, and a least-squares iterative technique for image reconstruction for single photon emission computed tomography (SPECT). The simulated SPECT geometry was of the pinhole aperture type, with 32 pinholes and 128 or 512 detectors. To test the robustness of the reconstruction techniques upon arbitrary geometries, a 360-detector geometry with a random pixel-detector-factor matrix was tested. Eight computer-simulated, 10-cm-diameter planar phantoms were used with 1961 2-mm(2) reconstruction bins and a range of 3000 to 50,000,000 detected photon counts. Reconstruction quality was measured by a normalized, squared error picture distance measure. Over a wide range of noise, the simulated annealing method had slightly better reconstruction quality than the iterative method, although requiring greater reconstruction time. Quenched annealing was faster than simulated annealing, with comparable reconstruction quality. Methods of efficiently controlling the simulated annealing algorithm are presented.     

Data-dependent bandwidth selection for emission computed tomography reconstruction

At present, the choice of bandwidth in emission computed tomography (ECT) reconstruction is done by subjective means. The authors develop an automated objective selection technique for linear reconstruction algorithms such as filtered backprojection. The approach is based on the method of unbiased risk estimation. A set of 2-D validation studies using computer simulated and physical phantom data from the Hoffman et al. (1990) brain phantom are carried out. These 2-D studies incorporate measured corrections for object attenuation and lack of uniformity in detector sensitivity. It is found that the unbiased risk approach works very well. Over a range of count rates and brain slice source distributions, the root mean square (RMS) error of the fully automated reconstruction, with the data-dependent choice of bandwidth, is around 5% greater than the RMS error for the reconstruction with an ideal choice of the bandwidth.     

Aperture collimation correction and maximum-likelihood image reconstruction for near-field coded aperture imaging of single photon emission computerized tomography

Coded aperture (CA) imaging originally developed in X-ray astronomy has not been widely used in nuclear medicine due to the decoding complexity of near-field CA images. In this paper, we present a near-field CA imaging technique and image reconstruction method for high sensitivity and high resolution single photon emission computerized tomography (SPECT). Our approach makes three contributions. First, a correction method for the aperture collimation effect is used to eliminate the near-field artifacts without dual acquisitions of mask and anti-mask images. Second, a maximum-likelihood expectation-maximization (MLEM) deconvolution method is used to restore CA images. Finally, a new MLEM-based algorithm is used to partially reconstruct three-dimensional (3-D) objects from a single projection of CA images. Experiments conducted using a dual-head SPECT system equipped with a parallel-hole collimator and a CA module show a tenfold increase in count sensitivity and significant improvement in image resolution with CA collimation as compared to parallel-hole collimation. Experiments conducted using the same dual-head SPECT system equipped with a pinhole collimator show that when the object is closer to the pinhole collimator the CA image resolution is only slightly inferior to the pinhole collimated image. We found that the MLEM deconvolution method provides an inherent nonnegativity constraint on pixel values and remarkably reduces background activities of CA images. The MLEM reconstruction algorithm for CA images is capable of reconstructing 3-D objects from a single projection and can be potentially extended to full 3-D SPECT reconstruction for CA images.     

Estimation of the local statistical noise in emission computed tomography

A simple modification of the filtered backprojection algorithm is presented for the computation of the local statistical noise in emission computed tomography. The technique is general in that any distribution of radioactivity may be accommodated. When applied to positron emission tomography, it is shown that the effects of photon absorption, random coincidences, radioactive decay, and detector nonuniformity may be included. Calculations have shown the effects of resolution, object size, and photon absorption on the statistical noise of disk-shaped emitters. Comparison of calculation and experiment show close agreement both in magnitude and spatial variation. Measurements of the noise level in tomograms of the brain obtained during continuous inhalation of 150-CO2 demonstrate that estimates of radioactivity concentration with a precision of a few percent are readily attainable.     

Failure analysis of ULSI circuits using photon emission

A real-time failure analysis technique for ULSI circuits using photon emission is proposed. This technique utilizes a photon detection system combined with a circuit tester. Improved failure detection is achieved because the tester can bias arbitrary blocks in the ULSI chip. Detecting and correct process defects and design errors improves the reliability of the ULSI chip     

Minimax emission computed tomography using high-resolutionanatomical side information and B-spline models

In this paper a minimax methodology is presented for combining information from two imaging modalities having different intrinsic spatial resolutions. The focus application is emission computed tomography (ECT), a low-resolution modality for reconstruction of radionuclide tracer density, when supplemented by high-resolution anatomical boundary information extracted from a magnetic resonance image (MRI) of the same imaging volume. The MRI boundary within the two-dimensional (2-D) slice of interest is parameterized by a closed planar curve. The Cramer-Rao (CR) lower bound is used to analyze estimation errors for different boundary shapes. Under a spatially inhomogeneous Gibbs field model for the tracer density a representation for the minimax MRI-enhanced tracer density estimator is obtained. It is shown that the estimator is asymptotically equivalent to a penalized maximum likelihood (PML) estimator with resolution-selective Gibbs penalty. Quantitative comparisons are presented using the iterative space alternating generalized expectation maximization (SAGE-FM) algorithm to implement the PML estimator with and without minimax weight averaging     

A general class of preconditioners for statistical iterativereconstruction of emission computed tomography

A major drawback of statistical iterative image reconstruction for emission computed tomography is its high computational cost. The ill-posed nature of tomography leads to slow convergence for standard gradient-based iterative approaches such as the steepest descent or the conjugate gradient algorithm. Here, new theory and methods for a class of preconditioners are developed for accelerating the convergence rate of iterative reconstruction. To demonstrate the potential of this class of preconditioners, a preconditioned conjugate gradient (PCG) iterative algorithm for weighted least squares reconstruction (WLS) was formulated for emission tomography. Using simulated positron emission tomography (PET) data of the Hoffman brain phantom, it was shown that the convergence rate of the PCG can reduce the number of iterations of the standard conjugate gradient algorithm by a factor of 2-8 times depending on the convergence criterion     

A practical method for position-dependent Compton-scatter correction in single photon emission CT

A new method is proposed to subtract the count of scattered photons from that acquired with a photopeak window at each pixel in each planar image of single-photon emission computed tomography (SPECT). The subtraction is carried out using two sets of data: one set is acquired with a main window centered at photopeak energy and the other is acquired with two subwindows on both sides of the main window. The scattered photons included in the main window are estimated from the counts acquired with the subwindows and then they are subtracted from the count acquired with the main windows. Since the subtraction is performed at each pixel in each planar image, the proposed method has the potential to be more precise than conventional methods. For three different activity distributions in cylinder phantoms, simulation tests gave good agreement between the activity distributions reconstructed from unscattered photons and those from the corrected data.     

Constrained Fourier space method for compensation of missing data in emission computed tomography

A method is introduced to compensate for missing projection data that can result from gas between detectors or from malfunctioning detectors. This method uses constraints in the Fourier domain to estimate the missing data, thus completing the data set so that the filtered backprojection algorithm can be used to reconstruct artifact-free images. The image reconstructed from estimates using this technique and a data set with gaps is nearly indistinguishable from an image reconstructed from a complete data set without gaps, using a simulated brain phantom.     

Developments with maximum likelihood X-ray computed tomography

An approach to the maximum-likelihood estimation of attenuation coefficients in transmission tomography is presented as an extension of earlier theoretical work by K. Lange and R. Carson (J. Comput. Assist. Tomography, vol.8, p.306-16, 1984). The reconstruction algorithm is based on the expectation-maximization (EM) algorithm. Several simplifying approximations are introduced which make the maximization step of the algorithm available. Computer simulations are presented using noise-free and Poisson randomized projections. The images obtained with the EM-type method are compared to those reconstructed with the EM method of Lange and Carson and with filtered backprojection. Preliminary results show that there are potential advantages in using the maximum likelihood approaches in situations where a high-contrast object, such as bone, is embedded in low-contrast soft tissue.     

Hybrid small animal imaging system combining magnetic resonance imaging with fluorescence tomography using single photon avalanche diode detectors

The high sensitivity of fluorescence imaging enables the detection of molecular processes in living organisms. However, diffuse light propagation in tissue prevents accurate recovery of tomographic information on fluorophore distribution for structures embedded deeper than 0.5 mm. Combining optical with magnetic resonance imaging (MRI) provides an accurate anatomical reference for fluorescence imaging data and thereby enables the correlation of molecular with high quality structural/functional information. We describe an integrated system for small animal imaging incorporating a noncontact fluorescence molecular tomography (FMT) system into an MRI detector. By adopting a free laser beam design geometrical constraints imposed by the use of optical fibers could be avoided allowing for flexible fluorescence excitation schemes. Photon detection based on a single-photon avalanche diode array enabled simultaneous FMT/MRI measurements without interference between modalities. In vitro characterization revealed good spatial accuracy of FMT data and accurate quantification of dye concentrations. Feasibility of FMT/MRI was demonstrated in vivo by simultaneous assessment of protease activity and tumor morphology in murine colon cancer xenografts.     

Automated image analysis for bone density measurements using computed tomography

Quantitative trabecular bone density (TBD) measurements in the appendicular skeleton, using computer tomography, are described. Pixel-value frequency histograms are generated, to determine the spatial coordinates of the centers of mass distribution for both bones in the image field. A line joining these centers is used as an axis for subsequent enhancement of horizontal image features, and for radial fan searches, to separate bone images in the analysis field. One bone image is then deleted and the outer contour of the remaining bone is determined using cross-correlation and mathematical morphology operators. This contour is then used as a template to calculate average linear attenuation coefficients (LACs) over 1-pixel-wide annuli for TBD calculation. Data from 33 individual subjects (1251 images) have been processed using both automatic and manual analysis methods. Both methods give the same numerical values for TBD, but the automatic method has slightly better precision. The analysis method is general and is adaptable to other imaging situations.