1. Introduction In the western world, vascular disorders form a major medical problem. To increase knowledge of the underlying mechanisms of, for example, atherosclerosis, extensive research is performed. At the university of Maastricht, a special type of microscopy is used for this task, called Two Photon Laser Scanning Microscopy (TPLSM). Using TPLSM, three dimensional images can be extracted from viable arteries [1]. To describe the processes occurring in the large arteries as a reaction on changing circumstances, a method is proposed for the estimation of the radius of vessels from TPLSM-images. Methods Algorithm The proposed algorithm is based on the Hough Transform; an evidence gathering algorithm that operates by means of voting for the best set of parameters. It is assumed that the cross-section of the vessel visible in the TPLSM-data represents a circle. A circle can be represented by: where the parameters x c, y c, and r represent the center coordinates and the radius of the circle respectively. Each combination of three non-colinear points uniquely define a circle. In the proposed algorithm, each combination of three points vote for a potential center (x c, y c ). Since a combination of points that lie far from each other give a more accurate fit, the vote is weighed by the distances between P 1, P 2 and P 3 : Votes are stored in a two dimensional array, in which the best fit is represented by the coordinates of the peak present in parameter space. Experiments To validate the proposed method, ten images are used. Images contain both parts of the wall, i.e. upper and lower part. This is needed for the determination of the true diameter of the vessel. Ground truth is formed by the manual estimation by 12 volunteers. The results are compared with a standard Least Squares Estimator (LSE) due to Zhou et al. [2]. Results Figure 2 displays the results of the proposed algorithm (red lines) and the LSE (blue lines) plot against the number of points used for the fits. The left column displays the average errors of the fits expressed in percents, the right column displays the standard deviation of the error. Top row represents the results when using points from one side of the wall, bottom row displays the result when taking both sides into account. Conclusions A method has been proposed for the estimation of the vascular diameter that, when using at least 100 data points, results in more stable estimates, compared to the standard Least Squares method. The standard deviation of the error is reduced by a factor of up to 5 times. References: [1] M. van Zandvoort et al. Two-Photon Microscopy for Imaging of the (Atherosclerotic) Vascular Wall. J. Vasc. Res. 2004;41:54-63 [2] J. Zhou et al. Algorithm of compensating loss of round color mark based on circle fitting. Proceedings of the IEEE International Conference on Mechatronics and Automation, pages 1397–1401, July 2005. Tools for Shape Analysis of Vascular Response using Two Photon Laser Scanning Microscopy J.W. van Triest BioMIM/Biomedical Image Analysis Figure 1 – Example of an Two Photon Laser Scanning Microscopy recording of a murine artery. Yellow indicates elastine, whereas blue indicates cell nuclei. Figure 2 – Results of the proposed algorithm (red lines) compared with standard Least Squares Estimator (blue lines).