Brain Tumor Detection Using Color-Based K-Means Clustering Segmentation

Authors:
Ming-Ni Wu;Chia-Chen Lin;Chin-Chen Chang
Affiliations:
-;-;-
Venue:
IIH-MSP '07 Proceedings of the Third International Conference on International Information Hiding and Multimedia Signal Processing (IIH-MSP 2007) - Volume 02
Year:
2007

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Abstract

In this paper, we propose a color-based segmentation method that uses the K-means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color-based segmentation algorithm with K-means is to convert a given gray-level MR image into a color space image and then separate the position of tumor objects from other items of an MR image by using K- means clustering and histogram-clustering. Experiments demonstrate that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.