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Brain Tumour Detection image segmentation using Machine Learning
Shilpa Sharma,  Nisha Mashahary,  Shashank Tripathi,  Harshit Sahay,  Deepak Kanojia
Image Processing is one of the most growing field in the biological images. MRI, CT scans and X-Ray are different types of images used in this technique. Even a minute deformity can be identified by these techniques. All these medical image processing uses and explores the 3D image datasheet of the human body for diagnosing pathologies or even to guide medical intervention such as surgical planning or research purpose. The most reliable form of biomedical image available tous is MRI as it does not expose the human body to any sorts of harmful radiation.Once the MRI is obtained it can be processed, and the part of brain affected by tumour can be segmented. The complete process of detecting brain tumour from an MRI can be classified into four different categories: Pre-Processing, Segmentation, Feature Extraction and Tumour Detection. This survey involves analysing andtaking help of the research by other professionals and compiling it into one paper.
Unique Identification Number - IJEDR2103007Page Number(s) - 46-48Pubished in - Volume 9 | Issue 3 | August 2021DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Shilpa Sharma,  Nisha Mashahary,  Shashank Tripathi,  Harshit Sahay,  Deepak Kanojia,   "Brain Tumour Detection image segmentation using Machine Learning"
, International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.9, Issue 3, pp.46-48, August 2021, Available at :http://www.ijedr.org/papers/IJEDR2103007.pdf