Volume 3, Issue 2, June 2013, Pages 560–569
Kalpana Saini1, M.L. Dewal2, and Manojkumar Rohit3
1 Deptt. of Electrical Engg., IIT Roorkee, India
2 Deptt. of Electrical Engg., IIT Roorkee, India
3 Deptt. of Cardiology, PGIMER Chandigarh, India
Original language: English
Copyright © 2013 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
In the present paper a novel region based active contour method is developed by formulating a new signed pressure force (SPF) function. The method has been applied to the echocardiographic images for getting the desired boundary. The method is useful for finding the automatic boundary detection of other images (Microbiological, MRI, CT, Natural and welding joint etc.) as well. Level set method in combination with original SPF has not been able to give satisfactory results during the segmentation of echocardiographic images. There are lots of noises present in the echocardiographic images those create difficulties in the segmentation process. The proposed method resolves all these difficulties in such a manner that the output image is having the proper boundary detection without any disturbances and noises. The very important advantage of this method is that it gives a very fast response in terms of time taken by CPU and the number of iterations. Fast response is very important in the clinical area especially in diagnosis purpose. The presented model is an advancement of Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method. Proposed model is more robust against images with weak edge and intensity inhomogeneity when compared with the performance of earlier methods.
Author Keywords: Echocardiographic, Active contour, Signed pressure force function, Level set, Segmentation, Gaussian filtering, Regularized level Set.
Kalpana Saini1, M.L. Dewal2, and Manojkumar Rohit3
1 Deptt. of Electrical Engg., IIT Roorkee, India
2 Deptt. of Electrical Engg., IIT Roorkee, India
3 Deptt. of Cardiology, PGIMER Chandigarh, India
Original language: English
Copyright © 2013 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In the present paper a novel region based active contour method is developed by formulating a new signed pressure force (SPF) function. The method has been applied to the echocardiographic images for getting the desired boundary. The method is useful for finding the automatic boundary detection of other images (Microbiological, MRI, CT, Natural and welding joint etc.) as well. Level set method in combination with original SPF has not been able to give satisfactory results during the segmentation of echocardiographic images. There are lots of noises present in the echocardiographic images those create difficulties in the segmentation process. The proposed method resolves all these difficulties in such a manner that the output image is having the proper boundary detection without any disturbances and noises. The very important advantage of this method is that it gives a very fast response in terms of time taken by CPU and the number of iterations. Fast response is very important in the clinical area especially in diagnosis purpose. The presented model is an advancement of Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) method. Proposed model is more robust against images with weak edge and intensity inhomogeneity when compared with the performance of earlier methods.
Author Keywords: Echocardiographic, Active contour, Signed pressure force function, Level set, Segmentation, Gaussian filtering, Regularized level Set.
How to Cite this Article
Kalpana Saini, M.L. Dewal, and Manojkumar Rohit, “Level set based on new Signed Pressure Force Function for Echocardiographic image segmentation,” International Journal of Innovation and Applied Studies, vol. 3, no. 2, pp. 560–569, June 2013.
