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Automatic MRI Brain Tumor Segmentation Techniques: A Survey

Otman Basir, Kalifa Shantta
DOI: http://dx.doi.org/10.21013/jas.v16.n2.p2
Abstract
Image segmentation plays a crucial role in recognizing image signification for checking and mining medical image records. Brain tumor segmentation is a complicated assignment in medical image analysis. It is challenging to identify precisely and extract that a portion of the image has abnormal tissues for further diagnosis and analysis. The method of segmenting a tumor from a brain MRI image is a highly concentrated medical science community field, as MRI is non-invasive. In this survey, brain MRI images' latest brain tumor segmentation techniques are addressed a thoroughgoing literature review. Besides, surveys the several approved techniques regularly applied for brain tumor MRI segmentation. Also, highlighting variances among them and reviews their abilities, pros, and weaknesses. Various approaches to image segmentation are described and explicated with the modern participation of several investigators.
Keywords
Magnetic Resonance Imaging, Atlas-based Segmentation, Classification, Thresholding Technique, Watershed Segmentation, Region growing
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