A mathematical algorithm for quantification of CT image noise.
Quantification of computed tomography ( CT) noise helps in determination of radiation dosage requirements for adequate image quality. Clinical methods used include calculation of the standard deviation ( SD) of a selected region of interest ( ROI). In industry, wavelet decomposition has been used fo...
| Publicado en: | Echocardiography Vol. 34; no. 1; pp. 116 - 119 |
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| Autores principales: | , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jan2017
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=120845912&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 120845912 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 07422822 GSE jtl: Echocardiography issn: 07422822 maglogo: Y pubinfo: dt: Jan2017 vid: 34 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 120845912 120845912 120845912 10.1111/echo.13389 120845912 ppf: 116 ppct: 3 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A mathematical algorithm for quantification of CT image noise. aug: au: Kerut, Edmund K. To, Filip Turner, Michael McKinnie, James Giles, Thomas affil: Heart Clinic of Louisiana, Marrero Louisiana sug: subj: Tomography, X-Ray Computed Radiation Dosage Calcinosis Digital Imaging Human Descriptive Statistics Data Analysis Software Goodness of Fit Chi Square Test Algorithms ab: Quantification of computed tomography ( CT) noise helps in determination of radiation dosage requirements for adequate image quality. Clinical methods used include calculation of the standard deviation ( SD) of a selected region of interest ( ROI). In industry, wavelet decomposition has been used for image compression while removing high-frequency noise. We evaluated a cohort of 74 consecutive patients referred for coronary artery calcium scoring and quantitated noise within a 16×16 ROI in the ascending aorta using the traditional SD method and also using a two-dimensional dyadic wavelet decomposition method. Clinically, noise has been shown to be proportional to patient weight and also body mass index ( BMI), which is a derived value from height and weight. Noise for both methods was plotted against patient parameters of height, weight, waist circumference and calculated BMI. A regression line was calculated and coefficient of determination (CoD) calculated for each. The CoD was better for height, weight, and waist circumference using the wavelet method as compared to the traditional SD method. The wavelet method of quantification of image noise may be an improved method as compared to the SD method. This method could help further refine an imaging system's determination of radiation dosage requirements to obtain a satisfactory quality image. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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