Comparison of color spaces for the severity analysis of mitral regurgitation

This paper looks at the adequacy of the four-color spaces i.e. RGB, L*A*B*, YCbCr, and CMY as far as their characterization execution in a computer helped arrangement framework for the severity analysis of mitral regurgitation into three categories i.e. mild, moderate, and severe. In order to evaluate the color space influence on the image analysis, texture features of the echocardiographic images have been extracted in different color spaces. These texture features are then utilized for training and testing purpose of the classifier i.e. support vector machine. The highest accuracy of 97.10 ± 1.06 using YCbCr color space in A2C view, 96.21 ± 0.88 and 97.37 ± 0.91 using RGB color space is achieved in A4C and PLAX views respectively. The outcomes indicate small but significant differences between color models with the ability to classify mitral regurgitation.

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