Brain Tumor Prediction through Behavior Analysis of Cells Growth Using Machine Learning Techniques

Elmitwally, Nouh and Freed, Muhammad Aqib and Iqbal, Muhammad Waseem and Ashraf, Aasma and Muneem, Farukh and Aqeel, Muhammad (2022) Brain Tumor Prediction through Behavior Analysis of Cells Growth Using Machine Learning Techniques. ICNGC 2022 Conference Proceedings. pp. 65-67.

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Abstract

Brain tumor is a very terrible disease. Brain tumor is caused by an increased number of cells. The presence of the skull layer around the brain makes it tough in studying the behavior of growth cells. It also raises the complication for the identification of disease. The initial discovery of a brain tumor is necessary to defend the survival of patients. Frequently, the brain cancer segmentation, and classification through the MRI images technique. Though, the radiologists are not providing actual visualization of brain cells in MRI images due to the irregular growth of cells, which forms of cells are growing rapidly and slow at some stage in brain tumors in the brain. So, automatic strategies are required to evaluate thoughts tumors exactly from MRI images in this research automatic, MRI brain tumors are used for classification, segmentation, and Behavior analysis of cell growth. The problem of visualization of cell growth and behavior analysis of brain cells is solved through MRI images which enhance the detection of cancer. To analyze the behavior of cell growth, which forms of cells are growing rapidly and slow at some stage in brain tumors, and analyze the area of images in which type of cells is affected. Single models are less efficient. We will use ensemble models which would also be helpful for better performance and accuracy.

Item Type:	Article
Dates:	Date Event 3 October 2022 Accepted 28 November 2022 Published Online
Uncontrolled Keywords:	MRI, CNN, SVM, Detection, Cancer
Subjects:	CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions:	Faculty of Computing, Engineering and the Built Environment > College of Computing
Depositing User:	Nouh Elmitwally
Date Deposited:	22 Nov 2022 11:37
Last Modified:	28 Nov 2022 16:14
URI:	https://www.open-access.bcu.ac.uk/id/eprint/13752

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