Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets
In this paper, an Ordered Subsets Expectation Maximization (OSEM) reconstruction algorithm based on Total Variation (TV) constraint was applied for sparse reconstruction of X-ray fluorescence CT. First, the Geant4 Monte Carlo code was used to simulate the imaging process of fan beam X-ray fluorescen...
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10829936/ |
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| author | Shanghai Jiang Le Chen Jie Zhong Li Ai Hua Yang Hong Lu |
| author_facet | Shanghai Jiang Le Chen Jie Zhong Li Ai Hua Yang Hong Lu |
| author_sort | Shanghai Jiang |
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| description | In this paper, an Ordered Subsets Expectation Maximization (OSEM) reconstruction algorithm based on Total Variation (TV) constraint was applied for sparse reconstruction of X-ray fluorescence CT. First, the Geant4 Monte Carlo code was used to simulate the imaging process of fan beam X-ray fluorescence CT imaging system based on parallel hole collimator. Then, the reconstructed image quality of the proposed algorithm with varying numbers of projections was evaluated using RMSE and CNR. Finally, the relationship between the number of subsets of the algorithm and the quality of the reconstructed image and the reconstruction time was explored. The results demonstrated that, compared with the conventional OSEM algorithm, the proposed OSEM algorithm based on Total Variation constraint has higher quality of reconstructed images at different projection numbers, and the reconstruction time of the algorithm decreases with the increase of subset, which achieves the purpose of improving the quality of the reconstructed image and reducing the reconstruction time when sparse reconstruction. |
| format | Article |
| id | doaj-art-0ab877eddb7d4f1dbfac9c58271f8ffe |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-0ab877eddb7d4f1dbfac9c58271f8ffe2025-01-15T00:02:20ZengIEEEIEEE Access2169-35362025-01-01137793780010.1109/ACCESS.2025.352669310829936Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered SubsetsShanghai Jiang0https://orcid.org/0000-0002-9690-1537Le Chen1https://orcid.org/0009-0008-3913-2576Jie Zhong2https://orcid.org/0009-0005-6338-6013Li Ai3https://orcid.org/0009-0004-9148-5521Hua Yang4Hong Lu5Department of Radiology, Seventh People’s Hospital of Chongqing, Central Hospital Affiliated to Chongqing University of Technology, Chongqing, ChinaChongqing Key Laboratory of Optical Fiber Sensor and Photoelectric Detection, Chongqing University of Technology, Chongqing, ChinaChongqing Key Laboratory of Optical Fiber Sensor and Photoelectric Detection, Chongqing University of Technology, Chongqing, ChinaDepartment of Radiology, Seventh People’s Hospital of Chongqing, Central Hospital Affiliated to Chongqing University of Technology, Chongqing, ChinaDepartment of Medical Imaging, Chongqing Traditional Chinese Medicine Hospital, Chongqing, ChinaDepartment of Radiology, Seventh People’s Hospital of Chongqing, Central Hospital Affiliated to Chongqing University of Technology, Chongqing, ChinaIn this paper, an Ordered Subsets Expectation Maximization (OSEM) reconstruction algorithm based on Total Variation (TV) constraint was applied for sparse reconstruction of X-ray fluorescence CT. First, the Geant4 Monte Carlo code was used to simulate the imaging process of fan beam X-ray fluorescence CT imaging system based on parallel hole collimator. Then, the reconstructed image quality of the proposed algorithm with varying numbers of projections was evaluated using RMSE and CNR. Finally, the relationship between the number of subsets of the algorithm and the quality of the reconstructed image and the reconstruction time was explored. The results demonstrated that, compared with the conventional OSEM algorithm, the proposed OSEM algorithm based on Total Variation constraint has higher quality of reconstructed images at different projection numbers, and the reconstruction time of the algorithm decreases with the increase of subset, which achieves the purpose of improving the quality of the reconstructed image and reducing the reconstruction time when sparse reconstruction.https://ieeexplore.ieee.org/document/10829936/X-ray fluorescence CTimage reconstructionMonte Carlo simulationsparse projectiontotal variation |
| spellingShingle | Shanghai Jiang Le Chen Jie Zhong Li Ai Hua Yang Hong Lu Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets IEEE Access X-ray fluorescence CT image reconstruction Monte Carlo simulation sparse projection total variation |
| title | Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets |
| title_full | Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets |
| title_fullStr | Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets |
| title_full_unstemmed | Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets |
| title_short | Reconstruction of Fan Beam X-Ray Fluorescence Computed Tomography Based on Parallel Hole Collimator via Total Variation and Ordered Subsets |
| title_sort | reconstruction of fan beam x ray fluorescence computed tomography based on parallel hole collimator via total variation and ordered subsets |
| topic | X-ray fluorescence CT image reconstruction Monte Carlo simulation sparse projection total variation |
| url | https://ieeexplore.ieee.org/document/10829936/ |
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