Coronary heart disease (CHD) is one of the world's most frequent causes of mortality and an important problem in medical practice. It is disease where one, two or all three coronary arteries are narrowed or obstructed mainly by atherosclerotic plaque(s). The consequence is diminished blood supply causing diminished oxygen supply of the dependent region of the myocardium, manifesting as angina pectoris. The most extreme consequences are myocardial infarction and cardiac death.

The object of project is collaboration in deployed plaque characterization algorithms and the patient-specific prediction model which can be enhanced with knowledge accumulated by heterogeneous data and resources. Blood element concentrations (e.g. LDL/HDL), patient medical condition (e.g. diabetic, hypertension), and patient habitual behavior (e.g. smoking/no smoking, exercising/no exercising) will be correlated with features extracted from patients medical images (e.g. MRI) and used for plaque characterization. The corresponding data will be situated in different repositories and even different systems. Both research groups will implement the treatment support system that will improve quality of medical services by providing cardiologists with suggestions on the best possible treatment scenario. The high-end expert system has a potential of application in medical practice (cardiology).