The OTSU THRESHOLD method is based on the analysis of the pixel histogram and is described by The ITK Software Guide as follows: "Another criterion for classifying pixels is to minimize the error of misclassification. The goal is to find a threshold that classifies the image into two clusters such that we minimize the area under the histogram for one cluster that lies on the other cluster’s side of the threshold. This is equivalent to minimizing the within class variance or equivalently maximizing the between class variance."
The Number of histogram bins defines the resolution of the histogram shape, whereas the Number of thresholds defines the number of distinct clusters. With the mouse CT, Otsu with the settings below finds appropriate thresholds for the skeleton object and the soft tissue, as illustrated below. Note that the threshold values can be inspected only after the actual segmentation by the View Otsu button.
Illustrated below is the rendering results of the two segments: the whole body segment rendered as a pink surface points with 0.9 blending level and the skeleton is rendered as a solid yellow surface with red wired frame on it: