Morphological Operations and its Analysis on Segmentation Techniques on Brain Cancer MRI by using Machine Learning

In developing countries cause of disease like brain cancer is effecting many people. Cancer is a disease where abnormal cells are produced without control and can affect other tissues, If it is identified at the early stage and treated appropriately then it can save human life. Brain Cancer MRI image processing is challenging field now a day. Brain cancer MRI processing and its analysis is act of examining images for identifying objects and analyzing their significance. Image segmentation is for detection of various kinds of unwanted cells and reviles the amount it spreads. Early detection and analysis of brain cancer is most difficult and time consuming task. Image segmentations refer to process of partitioning the image into multiple segments for locating objects and boundaries in image. This research paper presents practical implementation of morphological operations on brain cancer MRI using machine learning techniques and analysis on the effect of morphological operations on Brain Cancer MRI is done. In this paper practically implementation of various morphological operations like erosion, dilation, opening, closing and Morphological Gradient are done with the help of structuring element called as kernel. The implementation work is done by using python libraries. After applying morphological transformation minimum and maximum pixel intensity has been identified.