A GA based approach for boundary detection of left ventricle with echocardiographic image sequences

Ant Colony Optimization for Image Segmentation

“…In order to compare FGACO algorithm with others and test the influence of the new finite grade pheromone updating rule on optimization process, we select the boundary detection of left ventricle which is also considered in literature (Mishraa et al, 2003). A potentially good left ventricle image is selected as Fig.…”

“…A nonlinear mapping function is incorporated to transform the normalized gradient so that it discourages the contour to adhere to low gradient region (Mishraa et al, 2003).…”

“…However, we have implanted a preprocessing technique (Mishraa et al, 2003), such as, Gaussian and morphological, to detect an initial boundary followed by our ACO optimization procedure. A potentially good image is selected as Fig.…”

“…Experiments with different parameters are done for performance evaluation. Secondly, we compare the results of FGACO with general ACO and GA with left ventricle (Mishraa et al, 2003).…”

Analysis for Diagnosing Myocardial Ischemia by Detecting the Boundary of Left Ventricle in Echocardiography Sequences using GVF snake

“…The work in [1] presented a wavelet-based thresholding scheme for noise suppression in ultrasound images. In [2] the image is filtered by convolving with a 3X3 Gaussian low pass filter followed by thresholding and to eliminate the noise morphological dilation and erosion have been applied. Adaptive weighted median filter (AWMF) for reducing speckle noise in ultrasound images is presented in [3] which is based on the weighted median.…”