Influence of segmentation on micro-CT images of trabecular bone

Segmentation of biomedical images is of great importance in various studies aiming to both the identification of regions of interests within the image and the performance of quantified measurements. Nevertheless, the segmentation of the biomedical images represents a wide range of medical cases and there is not a unique technique applicable to all kinds of medical images. In this study, three popular techniques for segmenting micro-CT images of bone microstructures are evaluated. Fixed threshold, Otsu's algorithm and a modified version of the Chan-Vese segmentation technique have been applied on micro-CT images and have been compared to higher resolution golden standard, that is histological images. The modification of the Chan-Vese technique is based on the novel implementation of a new initialization process called the Branch Point Initialization. Stereological measurements were performed on all the segmented images and statistically compared to the golden standard. Fixed threshold and the modified Chan-Vese technique have shown comparable results, with a maximum significant error of about 10%. However, Chan-Vese showed an easier, faster and more reliable segmentation procedure for optimal settings identification. The Otsu's method showed a maximum error larger than 20%. Given the limits and advantages of the known segmentation techniques, the proposed modified Chan-Vese active contour technique shows high potential for use in the segmentation of micro-CT images as well as in other high-resolution X-ray images. This potential is augmented by the recent introduction of high-resolution clinical technologies for which standard techniques have already shown to be insufficient.