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OUP accepted manuscript. Eur Heart J Cardiovasc Imaging 2022; 23:944-955. [DOI: 10.1093/ehjci/jeac045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 02/19/2022] [Indexed: 11/12/2022] Open
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Mėlinytė K, Mizarienė V, Jurkevičius R. Long-term ischemic mitral regurgitation: which parameters predict decrease or increase in the degree after five years? Minerva Cardioangiol 2020; 68:237-245. [DOI: 10.23736/s0026-4725.20.05021-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Oguz D, Eleid MF, Dhesi S, Pislaru SV, Mankad SV, Malouf JF, Nkomo VT, Oh JK, Holmes DR, Reeder GS, Rihal CS, Thaden JJ. Quantitative Three-Dimensional Echocardiographic Correlates of Optimal Mitral Regurgitation Reduction during Transcatheter Mitral Valve Repair. J Am Soc Echocardiogr 2019; 32:1426-1435.e1. [DOI: 10.1016/j.echo.2019.06.014] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Revised: 06/19/2019] [Accepted: 06/19/2019] [Indexed: 12/24/2022]
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Abdul Khayum P, Sudheer Babu RP. Mitral Regurgitation Severity Analysis Based on Features and Optimal HE (OHE) with Quantification using PISA Method. JOURNAL OF INTELLIGENT SYSTEMS 2019. [DOI: 10.1515/jisys-2017-0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Heart disease is the foremost reason for death and also the main source of incapability in the developed nations. Mitral regurgitation (MR) is a typical heart disease that does not bring about manifestations until its end position. In view of the hidden etiologies of heart distress, functional MR can be partitioned into two subgroups, ischemic and no ischemic MR. A procedure is progressed for jet area separation and quantification in MR evaluation in arithmetical expressions. Thus, a strategy that depends on echocardiography recordings, image processing methods, and artificial intelligence could be useful for clinicians, particularly in marginal cases. In this research paper, MR segmentation is analyzed by the optimal histogram equalization (OHE) system used to segment the jet area. For a better execution of the work, threshold in HE was improved with the help of the krill herd optimization (KHO) strategy. With the MR quantification procedure, this segmented jet area was supported by the proximal isovelocity surface area (PISA); in this procedure, a few parameters in the segmentation were evaluated. From the results, this proposed methodology accomplishes better accuracy in the segmented and quantification method in contrast with the existing examination.
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