{"title":"康普顿相机x射线荧光成像设计及图像重建算法优化。","authors":"Shunmei Lu, Kexin Peng, Peng Feng, Cheng Lin, Qingqing Geng, Junrui Zhang","doi":"10.3390/jimaging11090300","DOIUrl":null,"url":null,"abstract":"<p><p>Traditional X-ray fluorescence computed tomography (XFCT) suffers from issues such as low photon collection efficiency, slow data acquisition, severe noise interference, and poor imaging quality due to the limitations of mechanical collimation. This study proposes to design an X-ray fluorescence imaging system based on bilateral Compton cameras and to develop an optimized reconstruction algorithm to achieve high-quality 2D/3D imaging of low-concentration samples (0.2% gold nanoparticles). A system equipped with bilateral Compton cameras was designed, replacing mechanical collimation with \"electronic collimation\". The traditional LM-MLEM algorithm was optimized through improvements in data preprocessing, system matrix construction, iterative processes, and post-processing, integrating methods such as Total Variation (TV) regularization (anisotropic TV included), filtering, wavelet-domain constraints, and isosurface rendering. Successful 2D and 3D reconstruction of 0.2% gold nanoparticles was achieved. Compared with traditional algorithms, improvements were observed in convergence, stability, speed, quality, and accuracy. The system exhibited high detection efficiency, angular resolution, and energy resolution. The Compton camera-based XFCT overcomes the limitations of traditional methods; the optimized algorithm enables low-noise imaging at ultra-low concentrations and has potential applications in early cancer diagnosis and material analysis.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 9","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12470824/pdf/","citationCount":"0","resultStr":"{\"title\":\"Compton Camera X-Ray Fluorescence Imaging Design and Image Reconstruction Algorithm Optimization.\",\"authors\":\"Shunmei Lu, Kexin Peng, Peng Feng, Cheng Lin, Qingqing Geng, Junrui Zhang\",\"doi\":\"10.3390/jimaging11090300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Traditional X-ray fluorescence computed tomography (XFCT) suffers from issues such as low photon collection efficiency, slow data acquisition, severe noise interference, and poor imaging quality due to the limitations of mechanical collimation. This study proposes to design an X-ray fluorescence imaging system based on bilateral Compton cameras and to develop an optimized reconstruction algorithm to achieve high-quality 2D/3D imaging of low-concentration samples (0.2% gold nanoparticles). A system equipped with bilateral Compton cameras was designed, replacing mechanical collimation with \\\"electronic collimation\\\". The traditional LM-MLEM algorithm was optimized through improvements in data preprocessing, system matrix construction, iterative processes, and post-processing, integrating methods such as Total Variation (TV) regularization (anisotropic TV included), filtering, wavelet-domain constraints, and isosurface rendering. Successful 2D and 3D reconstruction of 0.2% gold nanoparticles was achieved. Compared with traditional algorithms, improvements were observed in convergence, stability, speed, quality, and accuracy. The system exhibited high detection efficiency, angular resolution, and energy resolution. The Compton camera-based XFCT overcomes the limitations of traditional methods; the optimized algorithm enables low-noise imaging at ultra-low concentrations and has potential applications in early cancer diagnosis and material analysis.</p>\",\"PeriodicalId\":37035,\"journal\":{\"name\":\"Journal of Imaging\",\"volume\":\"11 9\",\"pages\":\"\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12470824/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/jimaging11090300\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/jimaging11090300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
Compton Camera X-Ray Fluorescence Imaging Design and Image Reconstruction Algorithm Optimization.
Traditional X-ray fluorescence computed tomography (XFCT) suffers from issues such as low photon collection efficiency, slow data acquisition, severe noise interference, and poor imaging quality due to the limitations of mechanical collimation. This study proposes to design an X-ray fluorescence imaging system based on bilateral Compton cameras and to develop an optimized reconstruction algorithm to achieve high-quality 2D/3D imaging of low-concentration samples (0.2% gold nanoparticles). A system equipped with bilateral Compton cameras was designed, replacing mechanical collimation with "electronic collimation". The traditional LM-MLEM algorithm was optimized through improvements in data preprocessing, system matrix construction, iterative processes, and post-processing, integrating methods such as Total Variation (TV) regularization (anisotropic TV included), filtering, wavelet-domain constraints, and isosurface rendering. Successful 2D and 3D reconstruction of 0.2% gold nanoparticles was achieved. Compared with traditional algorithms, improvements were observed in convergence, stability, speed, quality, and accuracy. The system exhibited high detection efficiency, angular resolution, and energy resolution. The Compton camera-based XFCT overcomes the limitations of traditional methods; the optimized algorithm enables low-noise imaging at ultra-low concentrations and has potential applications in early cancer diagnosis and material analysis.