BibTeX:

@article{IJIRSTV2I10042,
     title={Enhanced Implementation of Brain Tumor Detection using MRI},
     author={Manisha Takkekar, Eram Mulla, Mayur Rathod, Swapnil Shingole and Asha Rawat},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={10},
     pages={173--178},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I10042.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The primary aim of this paper is to improve the technique of brain tumor detection in order to provide more accuracy in tumor monitoring thereby enhancing the overall treatment. Brain tumor is one of the major cause of death of human beings. If the tumor is detected as early as possible there are high chances of survival in humans. Through this paper, we are trying to make a scenario possible for diagnostics, by creating an application which implements the concept of image segmentation, clustering, extraction and detection which will eventually present resultant data to the end user as well as diagnostics in the form of report enabling them to know about whether it is a tumor and if it a tumor then at what stage it is now. Image segmentation performs partitioning of an image into mutually exclusive regions. This article mainly emphasizes on detection of approximate location of tumor, and its stage. The algorithm will require 2D MRI of brain, which will be segmented into 2 parts i.e. left and right.

clustering, segmentation, brain tumor, region, processing, detection, analysis