SEMIAUTOMATIC SEGMENTATION OF VASCULAR NETWORK IMAGES USING A ROTATING STRUCTURING ELEMENT (ROSE) WITH MATHEMATICAL MORPHOLOGY AND DUAL FEATURE THRESHOLDING

Investigation of the physical dimensions of vascular network component s can enhance an understanding of the network's structure. The current study demonstrates a method for measuring the spatial concentration o f specific categories of vessels in a vascular network consisting of v essels of several diameters, lengths, and orientations. It is shown th at a combination of the mathematical morphology operation, opening, wi th a linear rotating structuring element (ROSE), and dual feature thre sholding can semi-automatically segment categories of vessels in a vas cular network. Specifically, capillaries and larger vessels (arteriole s and venules) are segmented in order to assess their spatial concentr ations. The ROSE algorithm generates the initial segmentation, and dua l feature thresholding provides a means of eliminating the nonedge art ifact pixels. The subsequent gray scale histogram of only the edge pix els yields the correct segmentation threshold value. This image proces sing strategy is demonstrated on micrographs of vascular casts. By adj usting the structuring element and rotation angles, this image process ing strategy could be applied to other network structures where a segm entation by network component categories is advantageous, but where th e objects can have any orientation.