SEGMENTATION OF ECHOCARDIOGRAPHIC IMAGES FOR MITRAL REGURGITATION EVALUATION

Abstract

The color Doppler echocardiography is used to detect the blood flow patterns, direction, and velocity in case of any abnormality such as valvular regurgitation and stenosis. In present days, the clinicians analyse the severity of mitral regurgitation (MR) by manually ascertaining regurgitant jet area with the assistance of cursor in the echocardiographic images. This paper focuses on automatic segmentation of the color mosaic pattern from echocardiographic images to determine the regurgitant jet area and finding its value in numerical terms. The evaluated jet area is then associated with the level of the severity of MR in particular mild, moderate and severe. For segmentation of echocardiographic images, the proposed strategy incorporates different segmentation algorithms like color space model, thresholding, and morphological operators. A total of 75 images have been examined taken from 25 patients suffering from MR. The severity of MR has been resolved in view of the regurgitant jet area got from the proposed technique and are compared with the manual method of assessment of MR. The algorithm developed is capable of removing the imitative areas during the process of segmentation. The regurgitant jet area acquired from the proposed strategy fulfils the clinical outcomes in the fast assessment of severity of MR