Detection of Heart Muscle Damage from Automated Analysis of Echocardiogram Video

Abstract

In this work, an approach for heart muscle damage detection from echocardiography sequences is proposed. To exemplify the approach, a system is presented which involves image denoising and enhancement and segmentation of the left ventricle (LV) for extracting the heart wall boundaries. Using the heart wall boundaries global LV parameters are calculated followed by statistical pattern recognition and classification to identify the heart muscle damage or myocardial ischemia (MI). The performance of this algorithm is assessed in 60 real patient data with both normal and abnormal conditions. The experimental results reveal that the proposed method can be used as an effective tool for detection of heart muscle damage or MI automatically.