Comparison of five different methods for obtaining the modulation transfer function of a diagnostic X-ray machine

Amr Al-Dhukair*, Nabil Maalej

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The modulation transfer function (MTF) of a modeled x-ray imaging machine was obtained using a point, a line, an edge, a variable frequency sine pattern and a random noise response functions. The MTFs and the system resolution were compared to the expected theoretical results. A rectangular focal spot with a uniform intensity was assumed as an x-ray photons source. The main source of blurring in the system was assumed to be the focal spot size. A linear system approximation and the convolution method were used to obtain the images of a point, a line, an edge, a sine pattern and random noise. The Fourier and other transformations were used to obtain the MTF and the limiting resolution of the system. Compared to the theoretical resolution results, the point, the line, the edge and the sine pattern methods gave a maximum error of 1%. The Wiener spectrum approach yielded the largest error of 40%. This large error is mainly due to the numerical uncertainty introduced by the autocorrelation of the noise response. Increasing the focal spot size and magnification reduced the system resolution in agreement with the theory.

Original languageEnglish
Title of host publicationIFMBE Proceedings
EditorsSun I. Kim, Tae Suk Suh
PublisherSpringer Verlag
Pages1353-1356
Number of pages4
Edition1
ISBN (Print)9783540368397
DOIs
StatePublished - 2007

Publication series

NameIFMBE Proceedings
Number1
Volume14
ISSN (Print)1680-0737
ISSN (Electronic)1433-9277

Bibliographical note

Publisher Copyright:
© International Federation for Medical and Biological Engineering 2007.

Keywords

  • Edgeresponse-function
  • Line-spread-function
  • MTF
  • Modulation transfer function
  • Pointspread-function

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

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