ABSTRACT: The most common cause of heart disease is narrowing or blockage of the coronary arteries, the blood vessels that supply blood to the heart itself. Early sign of heart disease will help you to choose the best treatment based on doctor recommendations to you. In an echocardiogram of heart, these echoes are turned into moving picture of your heart. Echocardiogram is a common test using sound wave map out shape and size of heart. This paper has focused on echocardiography where the decision is to detect the defect in the four chambers of heart quick. This work proposes to study Convolutional Neural Networks in medical science. It focuses on echocardiography. The term echocardiography means that the internal structure of a patient’s heart is studied through the images. The ultrasound waves create these images. The abnormalities in these images are found through echo. This work proposes to study Convolutional Neural Networks in medical science. It focuses on echocardiography. 2D echocardiogram is the test in which pictures of heart and various parts of heart are taken with the help of probe. The motive of this work is to decrease the overhead of the cardiologist. This approach will result in pointing the abnormality in the heart. Since, cardiologist and less experienced surgeons may take a while to figure out the defect or may miss the defect in the heart, this is a powerful approach which can detect even a little defect in heart which human eye tends to ignore.
Keywords: Convolutional neural network, Deep learning, Quality assessment, Echocardiography, Apical four-chamber, Machine Learning, Artificial Intelligence and Image Processing, etc.
| DOI: 10.17148/IJARCCE.2021.10749