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 ( < 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%) ( < 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.
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http://dx.doi.org/10.1155/2021/4383963 | DOI Listing |
Anal Chem
January 2025
Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-41061, United States.
Glow discharge optical emission spectrometry (GDOES) allows fast and simultaneous multielemental analysis directly from solids and depth profiling down to the nanometer scale, which is critical for thin-film (TF) characterization. Nevertheless, operating conditions for the best limits of detection (LODs) are compromised in lieu of the best sputtering crater shapes for depth resolution. In addition, the fast transient signals from ultra-TFs do not permit the optimal sampling statistics of bulk analysis such that LODs are further compromised.
View Article and Find Full Text PDFMagn Reson Med
January 2025
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
Purpose: To develop a deep subspace learning network that can function across different pulse sequences.
Methods: A contrast-invariant component-by-component (CBC) network structure was developed and compared against previously reported spatiotemporal multicomponent (MC) structure for reconstructing MR Multitasking images. A total of 130, 167, and 16 subjects were imaged using T, T-T, and T-T- -fat fraction (FF) mapping sequences, respectively.
Comput Vis ECCV
November 2024
University of Minnesota, Minneapolis.
Diffusion models have emerged as powerful generative techniques for solving inverse problems. Despite their success in a variety of inverse problems in imaging, these models require many steps to converge, leading to slow inference time. Recently, there has been a trend in diffusion models for employing sophisticated noise schedules that involve more frequent iterations of timesteps at lower noise levels, thereby improving image generation and convergence speed.
View Article and Find Full Text PDFPhys Med
January 2025
Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), 333 Techno Jungang-daero, Hyeonpung-eup, Dalseong-gun, Daegu, 42988, Republic of Korea. Electronic address:
Purpose: Material decomposition induces substantial noise in basis images and their synthesized computed tomography (CT) images. A likelihood-based bilateral filter was previously developed as a neighborhood filter that effectively reduces noise. However, this method is sensitive to image contrast, and the noise texture needs improvement.
View Article and Find Full Text PDFHigh-resolution non-line-of-sight (NLOS) imaging under nanosecond time-resolution conditions is challenging in applications. We propose a novel NLOS imaging method consisting of deconvolution modified iterative back projection and virtual modulated range migration for low time-resolution system, obtaining super-resolution (SR) histogram signal and high-resolution NLOS images sequentially. The proposed method is applicable to both confocal and non-confocal configurations.
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