The Value of Iterative Reconstruction of Algorithm-Based Coronary Artery Computed Tomography Imaging in the Diagnosis of Old Myocardial Infarction

The objective of this study was to compare the diagnostic value of computed tomography (CT) based on iterative reconstruction algorithm in old myocardial infarction (OMI), thereby providing theoretical guidance and practical basis for clinical treatment. In this study, in order to provide theoretical guidance and practical basis for the diagnosis and treatment of clinical OMI, 10 patients with OMI were selected and divided into two groups, with 5 patients in each group. In addition, an algebraic iterative reconstruction algorithm is constructed, which starts from the initial estimation value, compares, and corrects the estimation results and the measured results continuously until the error between the two results is less than the predetermined value. The experimental group was optimized by algebraic iterative reconstruction algorithm, and the control group was reconstructed by the hospital original method. The image quality parameters under different iteration times were analyzed and compared to obtain the optimal iteration times. The value of iterative reconstruction algorithm in clinical diagnosis was investigated by analyzing the time of drawing and the accuracy of diagnosis after drawing. Through the analysis and comparison of the image quality parameters of the patients from the experimental group, it was found that the image quality firstly increased with the increase in the number of iterations but decreased with the increase of the number of iterations after a certain number of iterations. The results showed that the optimal number of iterations was 13 times. The drawing time of the experimental group and the control group was 54.27 minutes and 117.87 minutes in turn, so the difference between the two groups was significant ( P < 0.05 ). Besides, there was a statistically marked difference in the accuracy rate of the experimental group (93.33%) and the control group (73.33%) ( P < 0.05 ). In conclusion, the time required for coronary artery CT imaging using algebraic iterative reconstruction algorithm was greatly reduced and the diagnostic accuracy was hugely improved. Therefore, the coronary artery CT imaging based on iterative reconstruction algorithm could make more effective use of medical resources and improve the diagnostic accuracy in the diagnosis of OMI.

Row Action Algebraic Reconstruction Techniques Implementation in Graphic Cards using SCILAB (Benchmark in Medical Imaging, Seismic Imaging and Walnut Imaging)

In this article we present a SCILAB implementation of algebraic iterative reconstruction methods for discretisation of inverse problems in imaging. These so-called row action methods rely on semi-convergence for achieving the necessary regularisation of the problem. We implement this method using SCILAB and provide a few simplified test problems: medical tomography, seismic tomography and walnut tomography.Numerical results show the capability of this method for the original and perturbed right-hand side vector.

Parallelization of Karcsmarz Algorithm using Graphic Cards for Seismic Imaging

We present a SCILAB implementation of algebraic iterative reconstruction methods for discretizations of inverse problems in seismic imaging. These so-called row action methods rely on semi-convergence for achieving the necessary regularization of the problem. We parallelize this method using NVIDIA graphics cards and SCILAB toolbox. We provide a few simplified test problems in seismic imaging to test those solver.