Blood vessels segmentation in retina: Preliminary assessment of the mathematical morphology and of the wavelet transform techniques

This work reports the development of a system for automatic analysis of retinal angiographic images. Particularly, we focus on the segmentation of the blood vessels in these images. We started by implementing a previously known technique based on mathematical morphology. Due to some shortcomings of this method to our data, we have developed a new approach based on the continuous wavelet transform using the Morlet wavelet. The main advantage of the latter with respect to our images lies in its capabilities in tunning to specific frequencies, thus allowing noise filtering and blood vessel enhancement in a single step. Furthermore, as we intend to use shape analysis techniques for the detection and quantitative characterisation of the vascular branching pattern in the retina, the wavelets will also be important with respect to performing fractal and multifractal image analysis. Nevertheless, it is worth mentioning that the mathematical morphology method was able to detect finer detail more precisely. Our present results suggest that an interesting direction to be investigated is how to use both approaches together in order to obtain better results and apply this as a diagnostic tool.