Comparison of the quality of temporal subtraction images obtained with manual and automated methods of digital chest radiography.


Journal Article

The authors have been developing a fully automated temporal subtraction scheme to assist radiologists in the detection of interval changes in digital chest radiographs. The temporal subtraction image is obtained by subtraction of a previous image from a current image. The authors' automated method includes not only image shift and rotation techniques but also a nonlinear geometric warping technique for reduction of misregistration artifacts in the subtraction image. However, a manual subtraction method that can be carried out only with image shift and rotation has been employed as a common clinical technique in angiography, and it might be clinically acceptable for detection of interval changes on chest radiographs as well. Therefore, the authors applied both the manual and automated temporal subtraction techniques to 181 digital chest radiographs, and compared the quality of the subtraction images obtained with the two methods. The numbers of clinically acceptable subtraction images were 147 (81.2%) and 176 (97.2%) for the manual and automated subtraction methods, respectively. The image quality of 148 (81.8%) subtraction images was improved by use of the automated method in comparison with the subtraction images obtained with the manual method. These results indicate that the automated method with the nonlinear warping technique can significantly reduce misregistration artifacts in comparison with the manual method. Therefore, the authors believe that the automated subtraction method is more useful for the detection of interval changes in digital chest radiographs.

Full Text

Duke Authors

Cited Authors

  • Katsuragawa, S; Tagashira, H; Li, Q; MacMahon, H; Doi, K

Published Date

  • November 1999

Published In

Volume / Issue

  • 12 / 4

Start / End Page

  • 166 - 172

PubMed ID

  • 10587911

Pubmed Central ID

  • 10587911

International Standard Serial Number (ISSN)

  • 0897-1889

Digital Object Identifier (DOI)

  • 10.1007/bf03168852


  • eng

Conference Location

  • United States