Date of Publication :10th April 2017
Abstract: Image segmentation is a process of partitioning a digital image into N regions. In today’s world, Brain tumor detection using image segmentation is fundamental but challenging problem in field of computer vision and image processing due to the diverse image content, image noise, non-uniform object texture and other factors. Accurate detection of size and location of brain tumor plays a vital role in the diagnosis of brain tumor. There are many image segmentation methods available for medical image analysis but the Region based and Clustering techniques are efficient, fast and accurate. This paper presents the two efficient image segmentation algorithms i.e. K-means and region growing techniques for brain MRI images and compare the two algorithms and determine the best one.
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