Segmentation of Brain Tumour and Its Area Calculation in Brain MR Images using K-Mean Clustering and Fuzzy C-Mean Algorithm
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2013, Vol 4, Issue 5
Abstract
This paper deals with the implementation of Simple Algorithm for detection of range and shape of tumour in brain MR images. Tumour is an uncontrolled growth of tissues in any part of the body. Tumours are of different types and they have different Characteristics and different treatment. As it is known, brain tumour is inherently serious and life-threatening because of its character in the limited space of the intracranial cavity (space formed inside the skull). Most Research in developed countries show that the number of people who have brain tumours were died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intracranial cavity produces a complete image of brain. This image is visually examined by the physician for detection & diagnosis of brain tumour. However this method of detection resists the accurate determination of stage & size of tumour. To avoid that, this project uses computer aided method for segmentation (detection) of brain tumour based on the combination of two algorithms. This method allows the segmentation of tumour tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it also reduces the time for analysis. At the end of the process the tumour is extracted from the MR image and its exact position and the shape also determined. The stage of the tumour is displayed based on the amount of area calculated from the cluster.
Authors and Affiliations
Mr. Rohit S. Kabade , Dr. M. S. Gaikwad
Keywords
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- EP ID EP151430
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