  Spatial and spatio-temporal model checking techniques have a wide range of
application domains, among which large scale distributed systems and signal and
image analysis. In the latter domain, automatic and semi-automatic contouring
in Medical Imaging has shown to be a very promising and versatile application
that can greatly facilitate the work of professionals in this domain, while
supporting explainability, easy replicability and exchange of medical image
analysis methods. In recent work we have applied this model-checking technique
to the (3D) contouring of tumours and related oedema in magnetic resonance
images of the brain. In the current work we address the contouring of (2D)
images of nevi. One of the challenges of treating nevi images is their
considerable inhomogeneity in shape, colour, texture and size. To deal with
this challenge we use a texture similarity operator, in combination with
spatial logic operators. We apply our technique on images of a large public
database and compare the results with associated ground truth segmentation
provided by domain experts.
