PubMed · 5014161
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I A England. 1972. Kompact 9 image intensifier.. https://pubmed.ncbi.nlm.nih.gov/5014161/
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Data which are sampled more densely than the Nyquist limit in k-space are weighted prior to reconstruction by the inverse of the local sampling density. This work considers the effects of weighting data that are sampled less densely than the Nyquist limit. It specifically analyzes azimuthally undersampled projection reconstruction, variable density spirals, and variable density phase encoding. Effects on resolution, aliasing, and SNR are given. Higher resolution is obtained by weighting undersampled data according to the inverse of sampling density, while better SNR and less aliasing artifact are obtained by weighting undersampled data uniformly. Magn Reson Med 43:867-875, 2000.
The three-dimensional (3D) object data obtained from a CT scanner usually have unequal sampling frequencies in the x-, y- and z-directions. Generally, the 3D data are first interpolated between slices to obtain isotropic resolution, reconstructed, then operated on using object extraction and display algorithms. The traditional grey-level interpolation introduces a layer of intermediate substance and is not suitable for objects that are very different from the opposite background. The shape-based interpolation method transfers a pixel location to a parameter related to the object shape and the interpolation is performed on that parameter. This process is able to achieve a better interpolation but its application is limited to binary images only. In this paper, we present an improved shape-based interpolation method for grey-level images. The new method uses a polygon to approximate the object shape and performs the interpolation using polygon vertices as references. The binary images representing the shape of the object were first generated via image segmentation on the source images. The target object binary image was then created using regular shape-based interpolation. The polygon enclosing the object for each slice can be generated from the shape of that slice. We determined the relative location in the source slices of each pixel inside the target polygon using the vertices of a polygon as the reference. The target slice grey-level was interpolated from the corresponding source image pixels. The image quality of this interpolation method is better and the mean squared difference is smaller than with traditional grey-level interpolation.
Computed tomography (CT) has been established as a major imaging modality in diagnostic radiology. Accordingly, acceptance testing and quality control of CT scanners is of great importance. While most procedures and phantoms for testing are widely accepted, there is still discussion and uncertainty about low-contrast (LC) sensitivity. In our opinion this unsatisfactory situation is caused at least in part by the lack of suitable phantoms for LC resolution measurements. We investigated the commonly used phantoms for LC detectability, the Catphan, and for LC resolution, the ATS phantom. While the Catphan showed stable object contrasts, the ATS phantom's measured contrast exhibited a strong dependence on temperature and x-ray quality. Based on newly developed polyurethane resin materials, we designed and tested a LC resolution phantom with several different contrast steps. The object contrasts showed no dependence on temperature and beam quality. The new LC resolution phantom proved to be very suitable for measuring a scanner's low-contrast sensitivity in the image plane, one of the most important image quality parameters. To assess LC resolution in three dimensions we designed an additional phantom with rows of spherical objects. A first prototype was evaluated in a multicenter study. The setup proved to be very helpful to quantify the in-plane and axial LC sensitivity of spiral CT scan modes.