A neuro-fuzzy system for automatic assessment of myocardial viability in positron emission tomography

A critical aspect of the treatment of patients with heart failure is the ability to predict the success of a revascularisation procedure. This prediction is based on the assessment of myocardial viability. Positron emission tomography is considered to be 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. More recent studies 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 for 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