Evolutionary algorithm for automatic detection of blood vessel shapes

Automatic detection of blood vessel shapes locating in the skin has a great diagnostic importance. In this work, an evolutionary approach operating on morphological operator and operation structures is proposed for the determination of the shape and network of blood vessels located in upper skin layers. A population of individuals comprising morphological structures is generated. A two-dimensional queue like data representation of individuals is applied in order to provide an appropriate representation of the connectivity constraints originated in the two dimensional nature of the structuring elements. Two-dimensional crossover and mutation type manipulation operations are carried out on selected elements of the population. Unlike the usual techniques, in our approach no constraints are used for background and smoothness as no matched filter or linear operator is applied. Also no a priori knowledge of the vessel shape is necessary due to the evolutionary method. Unlike the usual imaging techniques, that mainly use angiograms as input, in this work infrared filtered images taken by CCD camera are applied to investigate the blood vessels of broad skin areas. The method is implemented parallel on a lattice network of transputers resulting in a significantly decreased processing time compared to the usual techniques.