Application of Computed Tomographic Image Reconstruction Algorithms Based on Filtered Back-Projection in Diagnosis of Bone Trauma Diseases

2020 ◽  
Vol 10 (5) ◽  
pp. 1219-1224
Author(s):  
Xianyu Li ◽  
Yulin He ◽  
Qun Hua

Objective: To improve the diagnostic rate of bone trauma diseases by applying image reconstruction algorithm based on filtered back-projection to CT images of bone trauma. Methods: Sixty-three patients with bone trauma in our hospital were selected. After hospitalization, 63 patients took satisfactory localization images to make the lesions on the localization images close to or even exceed the resolution of conventional X-ray films. After scanning, the post-processing workstation software was used for post-processing of image reconstruction algorithm based on filtered back-projection. Finally, the diagnostic accuracy of X-ray plain film, common CT image and image examination based on filtered back-projection was compared statistically. Results: Among 63 cases of bone trauma, 48 cases were found by routine CT cross-sectional examination. The image reconstruction algorithm based on filtered back-projection was applied to all cases of wrist ulnar and trauma examination. The three-dimensional imaging can display the length, direction, shape of articular surface and fracture end of bone trauma as well as the size and spatial position of free small bone fragments stereoscopically and accurately. The relationship between bone trauma and placement. Discussion: Experiments show that when the projection data are complete, the filtering back-projection algorithm can reconstruct the image better, and the overall evaluation of the new filtering function is the best. Usually, the projection data are often incomplete, sometimes even seriously insufficient. At this time, it is necessary to adopt iterative reconstruction algorithm. However, no matter which algorithm is adopted, the reconstruction speed and accuracy are improved, and the quality of the reconstructed image is improved. It remains the direction of future efforts. The FBP method is the basic common algorithm for reconstructing image, and it is also the basis of many other algorithms. It is widely used in medical CT and other fields. Conclusion: The improved CT image reconstruction algorithm based on filtered back-projection has high application value in the diagnosis of bone trauma diseases. By comparing the three indexes of serial processing time, information transfer interface and image noise, the suspicious site of bone trauma can be diagnosed clearly. In recent years, with the popularization of CT and the emergence of spiral CT, it has a good guiding significance for defining clinical diagnosis and treatment.

2022 ◽  
pp. 1-13
Author(s):  
Lei Shi ◽  
Gangrong Qu ◽  
Yunsong Zhao

BACKGROUND: Ultra-limited-angle image reconstruction problem with a limited-angle scanning range less than or equal to π 2 is severely ill-posed. Due to the considerably large condition number of a linear system for image reconstruction, it is extremely challenging to generate a valid reconstructed image by traditional iterative reconstruction algorithms. OBJECTIVE: To develop and test a valid ultra-limited-angle CT image reconstruction algorithm. METHODS: We propose a new optimized reconstruction model and Reweighted Alternating Edge-preserving Diffusion and Smoothing algorithm in which a reweighted method of improving the condition number is incorporated into the idea of AEDS image reconstruction algorithm. The AEDS algorithm utilizes the property of image sparsity to improve partially the results. In experiments, the different algorithms (the Pre-Landweber, AEDS algorithms and our algorithm) are used to reconstruct the Shepp-Logan phantom from the simulated projection data with noises and the flat object with a large ratio between length and width from the real projection data. PSNR and SSIM are used as the quantitative indices to evaluate quality of reconstructed images. RESULTS: Experiment results showed that for simulated projection data, our algorithm improves PSNR and SSIM from 22.46db to 39.38db and from 0.71 to 0.96, respectively. For real projection data, our algorithm yields the highest PSNR and SSIM of 30.89db and 0.88, which obtains a valid reconstructed result. CONCLUSIONS: Our algorithm successfully combines the merits of several image processing and reconstruction algorithms. Thus, our new algorithm outperforms significantly other two algorithms and is valid for ultra-limited-angle CT image reconstruction.


2019 ◽  
Vol 133 ◽  
pp. S1119-S1120
Author(s):  
I. Peiro Riera ◽  
E. Fernandez-Velilla Ceprià ◽  
J. Quera Jordana ◽  
O. Pera Cegarra ◽  
N. Anton Comelles ◽  
...  

2013 ◽  
Vol 20 (4) ◽  
pp. 596-602 ◽  
Author(s):  
Anton Kachatkou ◽  
Nicholas Kyele ◽  
Peter Scott ◽  
Roelof van Silfhout

An imaging model and an image reconstruction algorithm for a transparent X-ray beam imaging and position measuring instrument are presented. The instrument relies on a coded aperture camera to record magnified images of the footprint of the incident beam on a thin foil placed in the beam at an oblique angle. The imaging model represents the instrument as a linear system whose impulse response takes into account the image blur owing to the finite thickness of the foil, the shape and size of camera's aperture and detector's point-spread function. The image reconstruction algorithm first removes the image blur using the modelled impulse response function and then corrects for geometrical distortions caused by the foil tilt. The performance of the image reconstruction algorithm was tested in experiments at synchrotron radiation beamlines. The results show that the proposed imaging system produces images of the X-ray beam cross section with a quality comparable with images obtained using X-ray cameras that are exposed to the direct beam.


2006 ◽  
Vol 72 (724) ◽  
pp. 1888-1894
Author(s):  
Michihiko KOSEKI ◽  
Shuhei HASHIMOTO ◽  
Shinpei SATO ◽  
Hitoshi KIMURA ◽  
Norio INOU

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