A detection method for streak artifacts and radiological noise in a non-uniform region in a CT image

Imai, Kuniharu; Ikeda, Mitsuru; Enchi, Yukihiro; Niimi, Takanaga

doi:10.1016/j.ejmp.2009.11.003

« Previous Next »Physica Medica: European Journal of Medical Physics
Volume 26, Issue 3 , Pages 157-165, July 2010

A detection method for streak artifacts and radiological noise in a non-uniform region in a CT image

Kuniharu Imai
- Department of Radiological Technology, Nagoya University School of Health Sciences, 1-20 Daikominami 1-chome, Higashi-ku, Nagoya, 461-8673, Japan
- Corresponding author. Tel.: +81 52 719 3114; fax: +81 52 719 1587.
Mitsuru Ikeda
- Department of Radiological Technology, Nagoya University School of Health Sciences, 1-20 Daikominami 1-chome, Higashi-ku, Nagoya, 461-8673, Japan
- Tel.: +81 52 719 1587; fax: +81 52 719 1587.
Yukihiro Enchi
- Department of Radiology, Osaka University Hospital, 2-15 Yamadaoka, Suita, Osaka, 565-0871, Japan
- Tel.: +81 6 6879 6812; fax: +81 6 6879 6814.
Takanaga Niimi
- Department of Radiological Technology, Nagoya University School of Health Sciences, 1-20 Daikominami 1-chome, Higashi-ku, Nagoya, 461-8673, Japan
- Tel.: +81 52 719 3114; fax: +81 52 719 1587.

Received 17 June 2009; received in revised form 13 November 2009; accepted 20 November 2009. published online 28 December 2009.

Abstract

By using the CT images obtained by subtracting two CT images acquired under the same conditions and slice locations, we have devised a method for detecting streak artifacts in non-uniform regions and only radiological noise components in CT images. A chest phantom was scanned using 16- and 64-multidetector row helical CT scanners with various mAs values at 120kVp. The upper lung slice image was employed as a target image for evaluating the streak artifacts and radiological noise. One hundred parallel line segments with a length of 80 pixels were placed on the subtracted CT image, and the largest CT value in each CT value profile was employed as a feature variable of the streak artifacts; these feature variables were analyzed with the extreme value theory (Gumbel distribution). To detect only the radiological noise, all CT values contained in the 100 line profile were plotted on normal probability paper and the standard deviation was estimated from the inclination of its fitted line for the CT value plots. The two detection methods devised in this study were able to evaluate the streak artifacts and radiological noise in the CT images with high accuracy.