Li, Hong Juang and Ming, Ni Wu (2010) MRI brain lesion image detection based on color-converted K-means clustering segmentation. Measurement, 43 (7). 941 - 949. ISSN 0263-2241
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Official URL: http://dx.doi.org/10.1016/j.measurement.2010.03.01...
We present a preliminary design and experimental results of tumor objects tracking method for magnetic resonance imaging (MRI) brain images (some stock images) that utilizes color-converted segmentation algorithm with K-means clustering technique. The method is capable of solving unable exactly contoured lesion objects problem in MRI image by adding the color-based segmentation operation. The key idea of color-converted segmentation algorithm with K-means is to solve the given MRI image by converting the input gray-level image into a color space image and operating the image labeled by cluster index. In this paper we investigate the possibility of employing this approach for image-based-MRI application. The application of the proposed method for tracking tumor is demonstrated to help pathologists distinguish exactly lesion size and region.
|Uncontrolled Keywords:||color-converted segmentation algorithm, K-means clustering technique, lesion, tumor|
|Subjects:||T Technology > TJ Mechanical engineering and machinery|
|Deposited By:||Liza Porijo|
|Deposited On:||29 Jun 2012 03:44|
|Last Modified:||08 Feb 2017 08:02|
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