Imaging examination plays an important role in the clinical diagnosis and treatment of diseases. Magnetic Resonance Imaging (MRI) is one of the imaging examinations, which has been widely used in clinic clinical practice. The non-Cartesian Radial sampling method is used to obtain the image data, and it is interpolated to the uniform Cartesian coordinates using the gridding algorithm and then reconstructed. Finally, using the ability of GPU parallel computing to improve the efficiency of the grid, shorten the reconstruction time, and expect to accelerate the image reconstruction speed. The experimental results also show that under the same conditions of other external conditions, compared with the CPU reconstruction, the acceleration ratio of GPU reconstruction has reached more than 12 times.
For industrial CT, the existing 3D measurement method based on industrial CT sequence imaging needs to be improved in terms of accuracy, speed and the degree of automation. In this context, based on the existing imaging measurement theory and taking the industrial CT sequence imaging as the experimental object, two volume measurement methods have been proposed this paper based on the industrial CT sequence imaging. This method was applied to carry out equal spacing stratified CT scan on three typical shapes of standard steel workpiece and Actual workpiece with inner cavity, and the obtained sequence fault imaging was measured and analyzed and verified. The experimental results show that the two measurement methods proposed in this paper improve the accuracy of measurement by two to three orders of magnitude and the accuracy of measurement is better than 1% compared with the existing volume measurement algorithm, which can meet the high precision requirements of the engineering application.
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