Automatic Segmentation of Putamen from Brain MRI
In this paper we present an automatic segmentation of the Putamen shape from brain MRI based on wavelets and a neural network. Firstly we detect the Putamen region slice by slice using 1D wavelet feature extraction. Then fuzzy c-means technology is combined with edge detection to segment the objects inside the Putamen region. Finally features are extracted from the segmented objects and fed into a neural network classifier in order to identify the Putamen shape. Experiment shows the segmentation results to be accurate and efficient.
KeywordsBrain Magnetic Resonance Image Automatic Segmentation Morphological Operation Canny Edge Detection Image Segmentation Technique
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