Performance Comparison of K-Means & Canny Edge Detection Algorithm on MRI Images

Provided by: Academy & Industry Research Collaboration Center
Topic: Software
Format: PDF
MRI segmentation plays a crucial role in many medical imaging applications .Various approaches are applied for the Segmentation of the MRI depending on the medical application, Image modality and other factors. The objective of this paper is to perform a segmentation process on MR images of the human Brain using K-means Algorithm and Canny Edge Detection Algorithm. K-means Clustering algorithm gives them the segmented image of an MRI having the same intensity regions. K-means Clustering segments all the three matters of the brain i.e. Grey matter, White matter and Dark matter. Also the edge detection algorithm is implemented that gives them the boundaries of the various regions of the MRI depending on scale and threshold values used for the segmentation.

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