Boris Perkhounkov, J. Stec, E. Sidky, Xiaochuan Pan
{"title":"用多项式模型的指数来估计透射测量的x射线光谱","authors":"Boris Perkhounkov, J. Stec, E. Sidky, Xiaochuan Pan","doi":"10.1117/12.2217100","DOIUrl":null,"url":null,"abstract":"There has been much recent research effort directed toward spectral computed tomography (CT). An important step in realizing spectral CT is determining the spectral response of the scanning system so that the relation between material thicknesses and X-ray transmission intensity is known. We propose a few parameter spectrum model that can accurately model the X-ray transmission curves and has a form which is amenable to simultaneous spectral CT image reconstruction and CT system spectrum calibration. While the goal is to eventually realize the simultaneous image reconstruction/spectrum estimation algorithm, in this work we investigate the effectiveness of the model on spectrum estimation from simulated transmission measurements through known thicknesses of known materials. The simulated transmission measurements employ a typical X-ray spectrum used for CT and contain noise due to the randomness in detecting finite numbers of photons. The proposed model writes the X-ray spectrum as the exponential of a polynomial (EP) expansion. The model parameters are obtained by use of a standard software implementation of the Nelder-Mead simplex algorithm. The performance of the model is measured by the relative error between the predicted and simulated transmission curves. The estimated spectrum is also compared with the model X-ray spectrum. For reference, we also employ a polynomial (P) spectrum model and show performance relative to the proposed EP model.","PeriodicalId":228011,"journal":{"name":"SPIE Medical Imaging","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"X-ray spectrum estimation from transmission measurements by an exponential of a polynomial model\",\"authors\":\"Boris Perkhounkov, J. Stec, E. Sidky, Xiaochuan Pan\",\"doi\":\"10.1117/12.2217100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There has been much recent research effort directed toward spectral computed tomography (CT). An important step in realizing spectral CT is determining the spectral response of the scanning system so that the relation between material thicknesses and X-ray transmission intensity is known. We propose a few parameter spectrum model that can accurately model the X-ray transmission curves and has a form which is amenable to simultaneous spectral CT image reconstruction and CT system spectrum calibration. While the goal is to eventually realize the simultaneous image reconstruction/spectrum estimation algorithm, in this work we investigate the effectiveness of the model on spectrum estimation from simulated transmission measurements through known thicknesses of known materials. The simulated transmission measurements employ a typical X-ray spectrum used for CT and contain noise due to the randomness in detecting finite numbers of photons. The proposed model writes the X-ray spectrum as the exponential of a polynomial (EP) expansion. The model parameters are obtained by use of a standard software implementation of the Nelder-Mead simplex algorithm. The performance of the model is measured by the relative error between the predicted and simulated transmission curves. The estimated spectrum is also compared with the model X-ray spectrum. For reference, we also employ a polynomial (P) spectrum model and show performance relative to the proposed EP model.\",\"PeriodicalId\":228011,\"journal\":{\"name\":\"SPIE Medical Imaging\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPIE Medical Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2217100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPIE Medical Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2217100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
X-ray spectrum estimation from transmission measurements by an exponential of a polynomial model
There has been much recent research effort directed toward spectral computed tomography (CT). An important step in realizing spectral CT is determining the spectral response of the scanning system so that the relation between material thicknesses and X-ray transmission intensity is known. We propose a few parameter spectrum model that can accurately model the X-ray transmission curves and has a form which is amenable to simultaneous spectral CT image reconstruction and CT system spectrum calibration. While the goal is to eventually realize the simultaneous image reconstruction/spectrum estimation algorithm, in this work we investigate the effectiveness of the model on spectrum estimation from simulated transmission measurements through known thicknesses of known materials. The simulated transmission measurements employ a typical X-ray spectrum used for CT and contain noise due to the randomness in detecting finite numbers of photons. The proposed model writes the X-ray spectrum as the exponential of a polynomial (EP) expansion. The model parameters are obtained by use of a standard software implementation of the Nelder-Mead simplex algorithm. The performance of the model is measured by the relative error between the predicted and simulated transmission curves. The estimated spectrum is also compared with the model X-ray spectrum. For reference, we also employ a polynomial (P) spectrum model and show performance relative to the proposed EP model.