Evaluation the Effect of Scanning Parameters on CT Number to Various Electron Densities Via the Taguchi Dynamic Analysis

碩士 === 中臺科技大學 === 醫學影像暨放射科學系暨研究所 === 102 === This study used Taguchi dynamic analysis to evaluate the effect of the assigned CT number of scanning parameters in CT simulator for different electron densities. The CT numbers of certain tissues were deviated largely if those were scanned under inapprop...

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Bibliographic Details
Main Authors: Yi, Juei-En, 易瑞恩
Other Authors: Pan, Lung-Kwang
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/23548601410833764401
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Summary:碩士 === 中臺科技大學 === 醫學影像暨放射科學系暨研究所 === 102 === This study used Taguchi dynamic analysis to evaluate the effect of the assigned CT number of scanning parameters in CT simulator for different electron densities. The CT numbers of certain tissues were deviated largely if those were scanned under inappropriate operative parameters, and caused fluctuation in the dose planning calculation in routine process. To further explore the optimal setting of various CT numbers for electron densities, the Catphan 404 module of Catphan 600 was adopted and scanned with various combinations of operative parameters according to the Taguchi dynamic analysis. In doing so, an eighteen groups of the combination of the six operative parameters were arranged to fulfill the Taguchi requirement. Seven materials with different densities was set in each group then evaluated the derived electron densities. To further suppress the uncertainties and increase the reproducibility, each material was measured three times in all groups. Thus, a total of 378 (18x7x3=378) measurements were accomplished in this work. The evaluated dominant factor that mainly affected the CT number was kVp, FOV and the minor factor was mA. Furthermore, the optimized recommendation of the factors was also confirmed by the ANOVA with over 99% confidence level. The optimized setting were: (1) 1 sec scan time, (2) 130 kVp, (3) 200 mA, (4) 40 cm FOV, (5) 3 mm thickness, (6) soft algorithm. The recommended combination of the factors could successfully reduce the uncertainties of the dose treatment planning.