Arterial radius estimation from microscopic data using a new algorithm for circle parameter estimation

We developed and tested a new method for automatic determination of vessel wall diameters from image stacks obtained using Two-photon Laser Scanning Microscopy (TPLSM) on viable arteries in perfusion flow chambers. To this extent, a new method has been proposed for estimating the parameters of a circle describing the inner diameter of the blood vessels. The new method is based on the Hough Transform and the observation that three points that are not co-linear uniquely define a circle. By only storing the estimated center location, the computational and memory costs of the Hough Transform can be greatly reduced. We tested the algorithm on twenty images and compared the result with a ground-truth established by human volunteers, and a standard Least Squares technique. With errors of 3-5%, the algorithm allows accurate estimation of the vessel diameters from image stacks containing only small parts of the vessel cross section. Combined with TPLSM imaging of anatomical vessel wall properties, potentially, the algorithm enables the correlation of structural and functional properties of large intact arteries simultaneously, without requirements for additional experiments.