Collection and fuzzy estimation of truth labels in glial tumour segmentation studies

In this work, we propose a novel behavioural comparison strategy specifically oriented to accuracy assessment in MRI glial
tumour segmentation studies. A salient aspect of the proposed strategy is the use of the fuzzy set framework in modelling
visual inspection and interpretation processes. In particular, a reference estimation strategy based on fuzzy connectedness
principles is designed to merge individual labels and produce a common segmentation. The estimation is based exclusively
on highly reliable partial information provided by experts. Interaction is then drastically limited compared with a complete
manual tracing, leaving the estimation of the complete segmentation to the fuzzy connectedness method. A set of
experiments was conceived and conducted to evaluate the contribution of the solutions proposed in the process of truth label
collection and reference data estimation. A comparison analysis was also developed to see whether our method could
constitute a worthy alternative to well-known and state-of-the-art solutions.