Abstract—The severity grade of mitral regurgitation is identified easily if the color jet area from the echocardiographic image can be segmented properly. However the echocardiographic images are having many difficulties in the segmentation because there are too many noises, like speckle noise, artifacts and the variations of the human body. The segmentation of the color jet area is a very difficult task. One more problem is that the echocardiographic images obtained from the echocardiographic machines are color images having the color jet inserted on these images. Here we proposed a new technique to solve this problem. There is a combination of two methods viz. Particle swarm optimization (PSO) and multilevel threshold selection (MTS) to separate out the mitral regurgitation jet area.

Index Terms—Mitral regurgitation, echocardiographic, particle swarm optimization, multilevel threshold, segmentation.

Kalpana Chauhan and M. L. Dewal are with Indian Institute of Technology Roorkee, Roorkee 247667, India.
Rajeev Kumar Chauhan is with Indian Institute of Technology Mandi, Mandi, 175001, India.
Manojkumar Rohit is with the Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India.

Cite:Kalpana Chauhan, M. L. Dewal, Rajeev Kumar Chauhan, Manojkumar Rohit, "Regurgitation Area Segmentation Using the Particle Swarm Optimization and Multilevel Threshold Selection," International Journal of Computer and Communication Engineering vol. 4, no. 4, pp. 282-289, 2015.