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The full-width at half-max (FWHM) criterion is often used for both manual and automatic quantification of the vessel diameter in medical images. The FWHM criterion is easy to understand and it can be implemented with low computational cost. However, it is well known that the FWHM criterion can give an over- and underestimation of the vessel diameter. In this paper, we propose a simple and original method to create an unbiased estimation of the vessel diameter based on the FWHM criterion and we compared the robustness to noise of several edge detectors. The quantitative results of our experiments show that the proposed method is accurate and precise in comparison to other (more complex) edge detectors, even for small vessels.

Gaussian derivatives are often used as differential operators to analyze the structure in images. In this paper, we will analyze the accuracy and computational cost of the most common implementations for differentiation and interpolation of Gaussian-blurred multi-dimensional data. We show that - for the computation of multiple Gaussian derivatives - the method based on B-splines obtains a higher accuracy than the truncated Gaussian at equal computational cost.