[Grouping of observer's visual characteristics on the basis of difference in the criteria of visual detection and selection of the fittest clustering method:verification of observer's group with radiologist-like visual characteristics].

Various clustering methods are used in cluster analyses, with each clustering method demonstrating unique advantages. Therefore, it is important to make the best use of the advantages each method provides. We have recognized that it is necessary in the evaluation of X-ray images to classify observers quantitatively according to visual characteristics (grouping of observers) and have clustered observers using the UPGMA method, which is one of the clustering methods.

[Classification of observer-groups with cluster analysis and the criteria of visual decision for each group].

It is important that the evaluation of X-ray images include the observer's visual characteristics. However, evaluations of X-ray images that include these characteristics are not performed because of the difficulty of quantitatively elucidating visual characteristics. In this study, we classified observers into groups (clusters) by the same criteria of visual decision, using cluster analysis (unweighted Pair-Group method using arithmetic averages), and evaluated X-ray images on the basis of this separation.