Automatic boundary detection and severity assessment of mitral regurgitation. (April 2023)

• Record Type: Journal Article
• Authors: Thanaraj, Santhiya; Balodi, Arun; Anand, R.S.; Rawat, Anurag
• Is Part Of: Biomedical signal processing and control. Volume 82(2023)
• Publication Date: 2023-04
• Subjects: Mitral regurgitation -- Segmentation -- Color space model -- Thresholding -- Morphological operators; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2023.104616
• Languages: English
• ISSNs: 1746-8094

Abstract

Abstract: The most prevalent disease, cardiovascular disease (CVD), has a high mortality rate among people. The prognosis of CVD depends on early diagnosis. In the event of any abnormality, such as valvular regurgitation and stenosis, the blood flow patterns, direction, and velocity are detected using the color Doppler echocardiography. Today's clinicians determine the regurgitant jet region manually in the echocardiographic images with the aid of a cursor to assess the severity of mitral regurgitation (MR). Manual tracing takes a lot of time and involves both intra and inter-personal variances. This research offers an automatic delineation technique to quantify the regurgitant jet area value to address this problem. The level of MR severity, specifically mild, moderate, and severe, is then connected to the analyzed jet area. The suggested approach combines various segmentation methods, such as color space model, thresholding, and morphological operators, for segmenting echocardiographic pictures. A total of 75 MR-related images from 25 individuals have been evaluated. In light of the regurgitant jet area identified by the suggested technique and contrasted with the manual way of MR assessment, the severity of MR has been assessed. The segmentation procedure can be segmented to remove the imitation areas using the established method. The regurgitant jet region collected using the suggested technique satisfies the clinical objectives in the quick evaluation of MR severity. Highlights: An Automated Segmentation for the severity analysis of mitral regurgitation. No manual delineation of regurgitant area. Reduces inter and intra-observer variability. Reduces the processing time of the clinician.