Moving slice septa and pseudo three-dimensional reconstruction for multi-ring PET

Frequency split metal artifact reduction (FSMAR) in computed tomography

PURPOSE

The problem of metal artifact reduction (MAR) is almost as old as the clinical use of computed tomography itself. When metal implants are present in the field of measurement, severe artifacts degrade the image quality and the diagnostic value of CT images. Up to now, no generally accepted solution to this issue has been found. In this work, a method based on a new MAR concept is presented: frequency split metal artifact reduction (FSMAR). It ensures efficient reduction of metal artifacts at high image quality with enhanced preservation of details close to metal implants.

METHODS

FSMAR combines a raw data inpainting-based MAR method with an image-based frequency split approach. Many typical methods for metal artifact reduction are inpainting-based MAR methods and simply replace unreliable parts of the projection data, for example, by linear interpolation. Frequency split approaches were used in CT, for example, by combining two reconstruction methods in order to reduce cone-beam artifacts. FSMAR combines the high frequencies of an uncorrected image, where all available data were used for the reconstruction with the more reliable low frequencies of an image which was corrected with an inpainting-based MAR method. The algorithm is tested in combination with normalized metal artifact reduction (NMAR) and with a standard inpainting-based MAR approach. NMAR is a more sophisticated inpainting-based MAR method, which introduces less new artifacts which may result from interpolation errors. A quantitative evaluation was performed using the examples of a simulation of the XCAT phantom and a scan of a spine phantom. Further evaluation includes patients with different types of metal implants: hip prostheses, dental fillings, neurocoil, and spine fixation, which were scanned with a modern clinical dual source CT scanner.

RESULTS

FSMAR ensures sharp edges and a preservation of anatomical details which is in many cases better than after applying an inpainting-based MAR method only. In contrast to other MAR methods, FSMAR yields images without the usual blurring close to implants.

CONCLUSIONS

FSMAR should be used together with NMAR, a combination which ensures an accurate correction of both high and low frequencies. The algorithm is computationally inexpensive compared to iterative methods and methods with complex inpainting schemes. No parameters were chosen manually; it is ready for an application in clinical routine.

The frequency split method for helical cone-beam reconstruction

A new approximate method for the utilization of redundant data in helical cone-beam CT is presented. It is based on the observation that the original WEDGE method provides excellent image quality if only little more than 180 degrees data are used for back-projection, and that significant low-frequency artifacts appear if a larger amount of redundant data are used. This degradation is compensated by the frequency split method: The low-frequency part of the image is reconstructed using little more than 180 degrees of data, while the high frequency part is reconstructed using all data. The resulting algorithm shows no cone-beam artifacts in a simulation of a 64-row scanner. It is further shown that the frequency split method hardly degrades the signal-to-noise ratio of the reconstructed images and that it behaves robustly in the presence of motion.

Exact and approximate algorithms for helical cone-beam CT

This paper concerns image reconstruction for helical x-ray transmission tomography (CT) with multi-row detectors. We introduce two approximate cone-beam (CB) filtered-backprojection (FBP) algorithms of the Feldkamp type, obtained by extending to three dimensions (3D) two recently proposed exact FBP algorithms for 2D fan-beam reconstruction. The new algorithms are similar to the standard Feldkamp-type FBP for helical CT. In particular, they can reconstruct each transaxial slice from data acquired along an arbitrary segment of helix, thereby efficiently exploiting the available data. In contrast to the standard Feldkamp-type algorithm, however, the redundancy weight is applied after filtering, allowing a more efficient numerical implementation. To partially alleviate the CB artefacts, which increase with increasing values of the helical pitch, a frequency-mixing method is proposed. This method reconstructs the high frequency components of the image using the longest possible segment of helix, whereas the low frequencies are reconstructed using a minimal, short-scan, segment of helix to minimize CB artefacts. The performance of the algorithms is illustrated using simulated data.

3D reconstruction for a multi-ring PET scanner by single-slice rebinning and axial deconvolution

A three-dimensional (3D) image reconstruction method, which was originally developed for a positron emission tomography (PET) system consisting of two rotating scintillation cameras, has now been implemented for a multi-ring PET scanner with retractable septa. The method is called 'single-slice rebinning with axial deconvolution' (SSAD), and can be described as follows. The projection data are sorted into transaxial 2D sinograms. Correction for the axial blurring is made by deconvolution in the sinograms. To obtain the axial spread functions, which depend on the activity distribution, 2D reconstruction is first made using a limited axial acceptance angle. The final 3D image is obtained by 2D reconstruction of transaxial planes. The method is simple but not approximate, has a modest memory requirement, and can be combined with different 2D techniques. Evaluations by Monte Carlo simulations and phantom studies have been made.

A performance study of 3D reconstruction algorithms for positron emission tomography

This paper investigates the statistical and systematic accuracy of five three-dimensional reconstruction algorithms for multi-ring PET scanners operated without septa: the reprojection method, the direct Fourier reconstruction, the FAVOR algorithm, and the single-slice and multi-slice rebinning algorithms. Simulated data of a uniform cylinder, of Gaussian sources, and of spherical sources are used to compare respectively the noise properties, the modulation transfer function, and the recovery coefficients of the algorithms. Brain scans reconstructed with the different algorithms are compared by calculating the linear regression of the mean values within regions of interest. The most significant observations are a slight loss of transaxial resolution with the reprojection algorithm in the external slices of the scanner, and increased noise in the images reconstructed using multi-slice rebinning.

Simulation studies on a pseudo-three-dimensional reconstruction algorithm for volume imaging in multi-ring PET

The imaging performance of a pseudo-three-dimensional (3D) reconstruction algorithm has been investigated. The algorithm is based on ID filtering followed by 3D backprojection. High- and low-frequency components of the image are reconstructed separately, and oblique projections are used only for reconstructing the high-frequency component. The cross talk between different slices due to oblique backprojection is eliminated by high-pass filtering. 'Variable filters', the cut-off frequencies of which are proportional to the tilt angles of projections, provide higher signal-to-noise ratio than 'fixed filters' with similar capability for cross-talk rejection. The maximum ring difference used in the reconstruction of each slice is extended as far as possible, while still satisfying the requirement that the total density of backprojection beams deposited in the slice is approximately uniform in the field of view. This allows the use of almost all available projection data to improve signal-to-noise ratio in peripheral slices. The root mean square noise of the reconstructed images evaluated with simulation studies is in good agreement with numerical calculations, and it is shown that the loss in signal-to-noise ratio caused by discarding the low-frequency component of oblique projections is negligibly small as long as suitable variable filters are used.