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

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3 Author(s)
Ming-Ni Wu ; Nat. Chung Cheng Univ., Chaiyi ; Chia-Chen Lin ; Chin-Chen Chang

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.

Published in:

Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on  (Volume:2 )

Date of Conference:

26-28 Nov. 2007