A REVIEW: BRAIN TUMOR SEGMENTATION USING K-MEANS CLUSTERING FOR DETECTION AND CALCULATION OF TUMOR AREA

S. P. Mahale, R. K. Kanhe

Abstract: The most challenging and emerging field is medical image processing. For the detection and identification of tumor in MRI of brain is implemented here. The traditional method for brain medical resonance imaging and the detection of tumor is done by human inspection which is operator dependent. Segmentation is done by operator in the clinical environment which is very tedious task and time consuming work. Segmentation of MRI of brain is complicated in this medical imaging field except few presented methods. Brain MRI can be divided into various regions mainly soft tissues like white matter, cerebrospinal fluid, gray matter etc. Using this process of segmentation, the location and size of tumor may be found evaluated. The present methodology proposed here consisting of preprocessing like removal of noise, process of segmentation and some morphological operations which are the basic steps in the image processing tool. Extraction and detection of tumor from brain MRI scan images is done by using k-means clustering method in MATLAB software.

Keywords: MRI (Magnetic Resonance Imaging), K-means Clustering.

DOI: https://doi.org/10.15623/ijret.2016.0507061