Relative importance of the error sources in Wiener restoration of scintigrams

A multiresolution restoration method for cardiac SPECT imaging

In this study we present a multiresolution based method for restoring cardiac SPECT projections. Original projections were decomposed into a set of sub-band frequency images by using analyzing functions localized in both the space and frequency domain. This representation allows a simple denoising and restoration procedure by discarding high-frequency channels and performing inversion only in low frequencies. The method was evaluated in bull's eye reconstructions of a realistic cardiac chest phantom with a custom-made liver insert and 99mTc liver-to-heart activity ratios (LHAR) of 0:1, 1.5:1, 2.5:1, and 3.5:1. The cardiac phantom in free air was used as the reference standard. Reconstructions were performed by filtered backprojection using (1) no correction; (2) restoration without attenuation correction; (3) attenuation correction without restoration; and (4) restoration and attenuation correction. The attenuation correction was carried out with the Chang's method for one iteration. Results were compared with those obtained using an optimized prereconstruction Metz filter. Quantitative analysis was performed by calculating the normalized chi-square measure and mean +/- s.d. of bull's eye counts. In reconstructions with high liver activity (LHAR > 2), attenuation correction without restoration severely distorted the polar maps due to the spill-over of liver activity into the inferior myocardial wall. Both restoration methods when combined with an attenuation correction compensated this artifact and yielded uniform polar maps similar to that of the standard reference. There was no visual or quantitative difference between the performance of Metz filtering and multiresolution restoration. However, the main advantage of the multiresolution method is that it states a more concise and straightforward approach to the restoration problem. Multiresolution based methods does not require information about the object image or optimization processes, such as in conventional nuclear medicine restoration filters. In addition, the method is easy to implement using DFT techniques and potentially can be extended to noniterative spatially shift-invariant restorations in SPECT.

Noniterative compensation for the distance-dependent detector response and photon attenuation in SPECT imaging

A filtering approach is described, which accurately compensates for the 2D distance-dependent detector response, as well as for photon attenuation in a uniform attenuating medium. The filtering method is based on the frequency distance principle (FDP) which states that points in the object at a specific source-to-detector distance provide the most significant contribution to specified frequency regions in the discrete Fourier transform (DFT) of the sinogram. By modeling the detector point spread function as a 2D Gaussian function whose width is dependent on the source-to-detector distance, a spatially variant inverse filter can be computed and applied to the 3D DFT of the set of all sinogram slices. To minimize noise amplification the inverse filter is rolled off at high frequencies by using a previously published Wiener filter strategy. Attenuation compensation is performed with Bellini's method. It was observed that the tomographic point response, after distance-dependent filtering with the FDP, was approximately isotropic and varied substantially less with position than that obtained with other correction methods. Furthermore, it was shown that processing with this filtering technique provides reconstructions with minimal degradation in image fidelity.

Quantitative single-photon emission computed tomography: basics and clinical considerations

Although quantitative single-photon emission computed tomography (SPECT) has been the goal of much research effort for a number of years, only recently has it received wide interest, especially for clinical applications. It has been increasingly recognized that the achievement of quantitative SPECT will increase the accuracy of measurements, such as dimensions of specific regions of interest, absolute amount of radioactivity, and dosimetry calculations, and substantially reduce reconstruction image artifacts and distortions, thus, greatly improving clinical diagnosis. This article provides a review of the definition of terms, major factors affecting SPECT quantitation and their degrading effects on SPECT image quality, and methods to compensate for these effects. Compensation methods include those that make certain approximations for ease of implementation and those that provide more accurate compensation by modeling the imaging process more exactly, usually at the cost of increased complexity and computational requirements. Different reconstruction and compensation methods may be compared through the use of phantom cardiac and brain SPECT studies. The clinical efficacy of the methods may be demonstrated by applying them to a clinical thallium-201 myocardial perfusion SPECT study. The results clearly demonstrate that, by modeling the imaging process and/or image degrading factors three-dimensionally, quantitative reconstruction and compensation methods provide the best image quality and quantitative accuracy. Important research efforts and developmental work being conducted currently to bring quantitative SPECT into routine clinical use are also discussed.

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.

Improved positron emission tomography quantification by Fourier-based restoration filtering

Positron emission tomography (PET) images are characterized by both poor spatial resolution and high statistical noise. Conventional methods to reduce noise, such as local weighted averaging, produce further deteriorations in spatial resolution, while the use of deconvolution to recover resolution typically amplifies noise to unacceptable levels. We studied the use of two-dimensional Fourier filtering to simultaneously increase quantitative recovery and reduce noise. The filter was based on inversion of the scanner's measured transfer function, coupled with high frequency roll-off. In phantom studies, we found improvements in both "hot" and "cold" sphere quantification. Compared with ramp-only filtering, improvements in hot spot recovery for the highest accuracy filter averaged 13.6% +/- 6.6% for spheres larger than 15 mm; improvements in cold spot recovery averaged 30.7% +/- 4.7%. At the same time, the noise was reduced by a factor of 3 compared with randomly filtering. Fourier-based image restoration filtering is thus capable of improving both accuracy and precision in PET.