A critical aspect of the treatment of patients with heart failure is the ability to predict the success of a revascularization procedure. This prediction is based on the assessment of myocardial viability. Positron Emission Tomography is considered the gold standard for myocardial viability studies. Most of these studies are still based on qualitative assessment of the extent and severity of the disease. Studies that are more recent quantify the extent of viable tissue manually using interactive software. In this work, an accurate automatic assessment method is presented. Our approach is based on neuro-fuzzy techniques. A self-organized radial basis function network has been implemented to image segmentation and parameter extraction, and an adaptive network-based fuzzy inference system is used to combine complementary information (myocardial perfusion and metabolism) to decide on myocardial viability. This work demonstrates the efficiency and accuracy of neuro-fuzzy techniques when carefully applied to viability assessment. It is an innovative approach to viability parametric image construction.