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Updated: Aug 30, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
[Classification of observer-groups with cluster analysis and the criteria of visual decision for each group]
Takanaga Niimi1, Kuniharu Imai, Kenichi Kamegai
1Department of Radiology, Nagoya Daini Red Cross Hospital.
Abstract:
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. Clinical application is also discussed. It was found that observer clustering caused a decrease in between-observer variation. Observers were grouped into two different categories: one with the characteristics of radiologists and the other with the characteristics of medical physicists. Our results indicated that the group with the characteristics of radiologists was suitable for the quality control (QC) of X-ray images.
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