Method to calculate frequency characteristics of reconstruction filter kernel in X-ray computed tomography

Kazuhiro Sato, Yu Tomita, Ryota Kageyama, Yumi Takane, Shingo Kayano, Haruo Saito

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A computed tomography (CT) image is generally reconstructed by a filtered back projection (FBP) algorithm. In an FBP algorithm, the image quality primarily depends on a reconstruction filter kernel. Although the details of the filter kernel are not disclosed to users, the frequency response of the filter kernel can theoretically be calculated using the relational formula of the filter kernel and the modulation transfer function (MTF) of the reconstruction algorithm (MTFA). In this study, we proposed a method to determine the frequency response of a filter kernel and verify its validity. Two clinical CT scanners were used to derive the filter kernel. The MTF was obtained and subsequently separated to the MTF of the scanner system and MTFA. Using the relational formula of the filter kernel and MTFA, we calculated the frequency response of the filter kernel. To verify the calculated result, we measured the noise power spectrum (NPS). Additionally, the filter kernel was calculated using the relational formula of the filter kernel and NPS. In both CT scanners, the filter kernels calculated by the two methods showed good agreement, and we confirmed the validity of the results and the effectiveness of the proposed method. Furthermore, the inherent image quality performance of the CT scanner could be clarified by the reconstruction filter kernel.

Original languageEnglish
JournalAustralasian Physical and Engineering Sciences in Medicine
DOIs
Publication statusAccepted/In press - 2019
Externally publishedYes

Keywords

  • Computed tomography
  • Image reconstruction
  • Modulation transfer function
  • Noise power spectrum
  • Reconstruction filter kernel

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Physics and Astronomy(all)

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