Automatic thresholding of three-dimensional microvascular structures from confocal microscopy images

We have combined confocal microscopy, image processing, and optimization techniques to obtain automated, accurate volumetric measurements of microvasculature. Initially, we made tissue phantoms containing 15-microm FocalCheck microspheres suspended in type I collagen. Using these phantoms we obtained a stack of confocal images and examined the accuracy of various thresholding schemes. Thresholding algorithms from the literature that utilize a unimodal histogram, a bimodal histogram, or an intensity and edge-based algorithm all significantly overestimated the volume of foreground structures in the image stack. Instead, we developed a heuristic technique to automatically determine good-quality threshold values based on the depth, intensity, and (optionally) gradient of each voxel. This method analyzed intensity and gradient threshold methods for each individual image stack, taking into account the intensity attenuation that is seen in deeper images of the stack. Finally, we generated a microvascular construct comprised of rat fat microvessel fragments embedded in collagen I gels and obtained stacks of confocal images. Using our new thresholding scheme we were able to obtain automatic volume measurements of growing microvessel fragments.