Automatic multiple threshold scheme for segmentation of tomograms

Tomographic reconstructions, which are generally gray-scale images, are often segmented as to extract quantitative information, such as the shape or volume of image objects. At present, segmentation is usually performed by thresholding. However, the process of threshold selection is somewhat arbitrary and requires human interaction. In this paper, we present an algorithmic approach for automatically selecting the segmentation thresholds by using the available tomographic projection data. Assuming that each material (i.e., tissue type) in the sample has a characteristic, approximately constant gray value, thresholds are computed for which the segmented image corresponds optimally with the projection data.