2008
DOI: 10.1007/s11517-008-0389-9
|View full text |Cite
|
Sign up to set email alerts
|

Determination of radiotherapy X-ray spectra using a screen-film system

Abstract: A method to determine the X-ray spectrum delivered by a medical linear accelerator is presented. This method consists of an analytical calculation of the primary spectrum using the Schiff bremsstrahlung cross-section formula. A correction factor that accounts for the scatter component of the spectrum is estimated by comparing the signal in two screen-film systems to a theoretical prediction using a model of energy deposition in such detectors. The model makes use of the quantum absorption efficiency and the av… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2009
2009
2016
2016

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(2 citation statements)
references
References 29 publications
0
2
0
Order By: Relevance
“…Answers to this question include the methods of Laplace transform pairs, [4][5][6] direct matrix inversion, 7,8 neural networks, 9 and iterative unfolding (including least-squares, expectationmaximization, and simulated annealing) with: (a) a priori spectral knowledge and smoothing constraints, [10][11][12][13][14][15][16][17] (b) regularization, [18][19][20][21] or (c) spectrum parameterization. [22][23][24][25][26][27][28][29][30][31][32][33] In this study, before approaching the unfolding issue, we first try to answer the more fundamental question: how can we make the transmission data themselves contain more (and accurate) spectral information? To this end, EGSnrc (Refs.…”
Section: Introductionmentioning
confidence: 99%
“…Answers to this question include the methods of Laplace transform pairs, [4][5][6] direct matrix inversion, 7,8 neural networks, 9 and iterative unfolding (including least-squares, expectationmaximization, and simulated annealing) with: (a) a priori spectral knowledge and smoothing constraints, [10][11][12][13][14][15][16][17] (b) regularization, [18][19][20][21] or (c) spectrum parameterization. [22][23][24][25][26][27][28][29][30][31][32][33] In this study, before approaching the unfolding issue, we first try to answer the more fundamental question: how can we make the transmission data themselves contain more (and accurate) spectral information? To this end, EGSnrc (Refs.…”
Section: Introductionmentioning
confidence: 99%
“…Thicktarget formulae use reasonable approximations to account for the spreading and slowing down of electrons in the target (Nordell and Brahme 1984, Findlay 1989, Desobry and Boyer 1991. A number of parameterized functional forms which are based on thick-target formulae have been proposed (Ahnesjö and Andreo 1989, Baker 1993, Harrison et al 1993, Garnica-Garza 2008, an example of which is function 3, which was proposed in the context of spectral unfolding from depth-dose curves. In this function, dσ br /dE| (x,E e ) is the bremsstrahlung cross-section for electrons of kinetic energy E e , where E e is the mean kinetic energy of the electron spectrum at depth x in the target.…”
mentioning
confidence: 99%