Abstract
Brain tumors affect the normal functioning of the brain and if not treated in time these cancerous cells may affect the other tissues, blood vessels, and nerves surrounding these cells. Today, a large population worldwide is affected by the precarious disease of the brain tumor. Healthy tissues of the brain are suspected to be damaged because of tumors that become the most significant reason for a large number of deaths nowadays. Therefore, their early detection is necessary to prevent patients from unfortunate mishaps resulting in loss of lives. The manual detection of brain tumors is a challenging task due to discrepancies in appearance in terms of shape, size, nucleus, etc. As a result, an automatic system is required for the early detection of brain tumors. In this paper, the detection of tumors in brain cells is carried out using a deep convolutional neural network with stochastic gradient descent (SGD) optimization algorithm. The multi-classification of brain tumors is performed using the ResNet-50 model and evaluated on the public Kaggle brain-tumor dataset. The method achieved 99.82% and 99.5% training and testing accuracy, respectively. The experimental result indicates that the proposed model outperformed baseline methods, and provides a compelling reason to be applied to other diseases.
Subject
General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)
Reference36 articles.
1. The Bcl2 family: Regulators of the cellular life-or-death switch;Cory;Nat. Rev. Cancer,2002
2. Emerging connectivity of programmed cell death pathways and its physiological implications;Bedoui;Nat. Rev. Mol. Cell Biol.,2020
3. Pyroptosis versus necroptosis: Similarities, differences, and crosstalk;Frank;Cell Death Differ.,2019
4. Influence of the tumor microenvironment on NK cell function in solid tumors;Melaiu;Front. Immunol.,2019
5. Vanderah, T., and Gould, D. (2020). Nolte’s The Human Brain E-Book: An Introduction to its Functional Anatomy, Elsevier Health Sciences.
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