title: The application of Markov theory to contrast-detail analysis.
abstract: OBJECTIVE
  To improve the accuracy of contrast-detail (C-D) analysis, we have devised a new evaluation method of the detection performance in the C-D analysis by using the Markov process model. This article describes this new evaluation method and the results of applying it to the illustrative examples.
  
  
  METHODS
  A commercially available C-D phantom was employed as a test object, and 20 phantom radiographs with an average background density of 0.8 were prepared. Thirty-five observers interpreted all phantom radiographs independently of each other with the room lights off. We assume the Markov model in which the selection of the smallest visible contrast for each row of disks with the same diameter depends only on the contrast selected as the smallest visible one for the same row in the just-before reading experiment. By using this Markov model, the contrast detectability for each disk diameter was calculated, and a C-D diagram was constructed based on these results. The conventional C-D diagram was also derived from the averages of contrast detectability obtained from the interpretations of all phantom radiographs.
  
  
  RESULTS
  All C-D diagrams obtained from our devised method agreed well with each other and were in good accord with the conventional C-D diagram from the interpretations of all phantom radiographs.
  
  
  CONCLUSIONS
  We have devised a new evaluation method of C-D analysis by using the Markov model and have shown this method will be consistent with the conventional evaluation method in the C-D analysis.
authors.affiliation: Department of Radiological Technology, Nagoya University School of Health Sciences, Higashi-ku, Nagoya 461-8673, Japan. imai@met.nagoya-u.ac.jp
authors.forename: Kuniharu
authors.initials: K
authors.lastname: Imai
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Ikeda
authors.forename: Takanaga
authors.initials: T
authors.lastname: Niimi
mesh_terms: D000704:Analysis of Variance; D003287:Contrast Media; D006801:Humans; D016247:Information Storage and Retrieval; D008390:Markov Chains; D015588:Observer Variation; D019047:Phantoms, Imaging; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods / Q000592:standards; D011859:Radiography / Q000379:methods / Q000592:standards; D015203:Reproducibility of Results; D012107:Research Design; D013647:Task Performance and Analysis
chemical_list: D003287:Contrast Media