  A manual measurement of blood vessels diameter is a conventional component of
routine visual assessment of microcirculation, say, during optical
capillaroscopy. However, many modern optical methods for blood flow
measurements demand the reliable procedure for a fully automated detection of
vessels and estimation of their diameter that is a challenging task.
Specifically, if one measure the velocity of red blood cells by means of laser
speckle imaging, then visual measurements become impossible, while the
velocity-based estimation has their own limitations. One of promising
approaches is based on fast switching of illumination type, but it drastically
reduces the observation time, and hence, the achievable quality of images. In
the present work we address this problem proposing an alternative method for
the processing of noisy images of vascular structure, which extracts the mask
denoting locations of vessels, based on the application of the continuous
wavelet transform with the Morlet wavelet having small central frequencies.
Such a method combines a reasonable accuracy with the possibility of fast
direct implementation to images. Discussing the latter, we describe in details
a new MATLAB program code realization for the CWT with the Morlet wavelet,
which does not use loops completely replaced with element-by-element operations
that drastically reduces the computation time.
