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In today's world, increasing life expectation have made the heart failures of important concern. For clinical diagnosis, parameters for the condition of heart are needed. Accurate and fast image segmentation algorithms are of paramount importance prior to the calculation of these parameters. An automatic method for segmenting the cardiac magnetic resonance (CMR) images is always desired to increase the accuracy. We prefer random walk method due to its noise robustness and unconditional approach over other segmentation algorithms. Performance of the method solely depends on the selection of initial seeds, which uses to be decided manually. But there are some hurdles while applying this method to CMR images, due to their color complexity unlike general images. So the main objective to select the number and placement of seeds automatically. We obtain this with use of cantilever beam (CB) equation in association with a variable threshold technique. The highlight of our method is its ability to succeed with minimum number of initial seeds.
Date of Conference: 9-11 Dec. 2009