“Brain Image Segmentation using Expectation Maximization and K-Nearest Neighbor Algorithms”
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Pulchowk Campus
Abstract
Segmentation of an image entails the division or separation of the image into
regions of similar attribute. Segmentation is one of the main problems in image
analysis. Expectation Maximization (EM) and K-Nearest Neighbor (KNN)
Algorithms have been used for segmentation of Magnetic Resonance (MR) image of
brain.
The main objective of this thesis is to segment and classify brain image into
Gray Matter (GM), White Matter (WM) and Cerebral Spinal Fluid (CSF) using EM
algorithm and KNN algorithm.
Description
Segmentation of an image entails the division or separation of the image into
regions of similar attribute.
Citation
Master of Science in Information and Communication Engineering