Functional magnetic resonance imaging: Comparison between activation maps and computation pipelines in a clinical context

In this study new evaluation strategies for comparing different Statistical Parametric Maps computed from fMRI time-series analysis software tools are proposed. The aim of our work is to assess and quantitatively evaluate the statistical agreement of activation maps. Some pre-processing steps are necessary to compare SPMs (Statistical Parametric Maps), including segmentation and co-registration. The study of the statistical agreement is carried out following two ways. The first way considers SPMs as the result of two classification processes and extracts confusion matrix and Cohen's kappa index to assess agreement. Some considerations will be made on the statistical dependence of classes and a new formulation of kappa index will be used for overcoming this problem. The second way considers SPMs as two 3D images, and computes the similarity of SPMs images with a fuzzy formulation of the Jaccard Index. Several experiments were conducted both to assess the performance of the proposed evaluation tools and to compare activation maps computation pipelines from two widely used software tools in a clinical context.