to download project abstract


Accurate segmentation of cardiac bi-ventricle (CBV) from magnetic resonance (MR)
images has a great significance to analyze and evaluate the function of the
cardiovascular system. However, the majority of cardiac MR images show that the
similar intensity distribution in different regions, thus providing a little edge information.
In this proposed system the input images are color images means then we convert to
gray scale from the color images. The image features like color, weight, and depth
and pixel information to apply before the classifier (neural network). The ROI (Region
of interest) segmentation algorithm is used in order to detect segment the portion of
defected areas. The back propagation neural network concept is used for training the
image and testing the image with the help of weight estimating classifier.

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