String matching techniques for high-level primitive formation in 2-D vascular imaging.
This paper deals with a so-called "intermediate" description, in other words, the formation of high-level primitives in angiographies. The method is based on an attributed string matching technique capable to capture the shape similarities between low-level primitives (i.e., vessel contours and centerlines). After designing a multiparametric cost function, we propose a multiline pairing algorithm. In order to objectively evaluate its performances, results are first provided on simulated data and then on a set of coronarographic images, where it is shown that anatomically coherent entities like vessel segments and branches can be built, "objects" that can be further individually analyzed for clinical purpose.
Algorithms↗