An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

In-vivo dynamic visualization and accurate quantification of vascular networks is a prerequisite of crucial importance in both therapeutic angiogenesis and tumor anti-angiogenesis studies. A user independent computerized tool was developed, for the automated segmentation and quantitative assessment of in-vivo acquired DSA images. Automatic vessel assessment was performed employing the concept of image structural tensor. Initially, vasculature was estimated according to the largest eigenvalue of the structural tensor. The resulted eigenvalue matrix was treated as gray-matrix from which the vessels were gradually segmented and then categorized in three main sub-groups; large, medium and small-size vessels. The histogram percentiles, corresponding to 85%, 65% and 47% of prime eigenvalue gray-matrix were optimally found to give the thresholds T1, T2 and T3 respectively, for extracting vessels of different size. The proposed methodology was tested on a series of DSA images in both normal rabbits (group A) and in rabbits 1Corresponding author. c © 2009 IOP Publishing Ltd and SISSA doi:10.1088/1748-0221/4/05/P05014 2 0 0 9 J I N S T 4 P 0 5 0 1 4 with experimental induced chronic hindlimb ischemia (group B). As a result an automated computerized tool was developed to process images without any user intervention in either experimental or clinical studies. Specifically, a higher total vascular area and length were calculated in group B compared to group A (p=0.0242 and p=0.0322 respectively), which is in accordance to the fact that significantly more collateral arteries are developed during the physiological response to the stimuli of ischemia.