Digital Image Processing for Determining the Speed of Blood Flow in the Heart Based on the Doppler Effect

Abstract

A research study was conducted to estimate and visualize 2D vectors of blood flow in the heart using image processing algorithms to determine Doppler velocity at each point. The study used secondary data from ten patients who provided informed consent, encompassing healthy and unhealthy hearts. ECD image data were collected using a Philips epiq 7C machine in DICOM format. The image processing tasks, including area segmentation, flow velocity analysis, and area smoothing, were carried out using MATLAB R2016b software. These processes aimed to eliminate noise and other disturbances, enhancing the accuracy of blood flow velocity estimation in the heart. The study's findings included estimations and 2D vector visualizations representing the average blood flow velocity at each point within the heart. These achievements were made possible using image processing techniques to correct the acquired images, ensuring precise measurement of blood flow speed. Among the collected data, one patient exhibited indications of a healthy heart, with an average blood flow velocity of 40.2513 cm/s, a maximum speed of 68.5807 cm/s, and a minimum speed of 33.6971 cm/s. Deviations from the normal range of blood flow speeds were considered as potential abnormalities in heart health.