Comparison of classification techniques for the assessment of myocardial viability by cardiac imaging with delayed MR enhancement

Myocardial viability is a fundamental question in clinical decision making process and in the treatment of ischemic heart disease. Contrast enhanced Magnetic Resonance can distinguish between viable and necrotic myocardium in non-invasive manner and with excellent definition of endocardial and epicardial tissue, allowing to assess the extent of necrosis. The correct classification between pathological and healthy tissue is a fundamental process for the posterior quantification and diagnosis. Using image processing theory is possible to use automatic techniques for tissue classification; however it is difficult to choose which is better. In this paper we present a semiautomatic methodology that allows the quantification of myocardial viability in MR delayed enhancement. We evaluate the accuracy and concordance of different classification algorithms comparing the results with simulated data and with the classification of expert radiologists. It was not significant differences in the Fuzzy C-means and K-means results. The threshold classification method showed high sensibility but very low agreement. We concluded that either of the centroid-based algorithms, the Fuzzy C-means or the K-means are correct for the assessment of myocardial viability.