title: [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].
abstract: 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. We found that the observers were clustered into two different groups, one with radiologist-like characteristics and the other with medical physicist-like characteristics. Furthermore, we suggested that the group with radiologist-like characteristics was suitable for QC of X-ray images. However, it is doubtful whether the UPGMA method is most suitable for the grouping of observers. In this work we clustered observers using various clustering methods and examined the most suitable method for the evaluation of X-ray images. The results showed that the ward method was least suitable for the grouping of observers, and they were distinctly grouped into two different categories by using a further method.
authors.affiliation: Department of Radiology, Nagoya Daini Red Cross Hospital.
authors.forename: Takanaga
authors.initials: T
authors.lastname: Niimi
authors.forename: Kuniharu
authors.initials: K
authors.lastname: Imai
authors.forename: Kenichi
authors.initials: K
authors.lastname: Kamegai
authors.forename: Takeshi
authors.initials: T
authors.lastname: Hioki
authors.forename: Akihiro
authors.initials: A
authors.lastname: Mano
mesh_terms: D016000:Cluster Analysis; D016001:Confidence Intervals; D006801:Humans; D015588:Observer Variation; D019047:Phantoms, Imaging; D010820:Physicians; D011859:Radiography; D011871:Radiology