Paper Key : IRJ************722
Author: Sumeet Tejbahadur Asha Yadav
Date Published: 16 Oct 2023
Abstract
A brain tumor is an irregular growth of cells within the brain. These growths can be either non-cancerous (benign) or cancerous (malignant). They may originate within the brain (primary tumors) or result from cancer cells spreading to the brain from other parts of the body (metastatic tumors). Brain tumor symptoms can vary depending on their size and location and may include headaches, seizures, personality changes, and neurological issues. Treatment options include surgery, radiation therapy, and chemotherapy, depending on the tumor's type and stage. Detecting and treating brain tumors early can significantly impact a patient's prognosis. Hence trusted and automatic classification schemes are essential to prevent the death rate of humans. Automatic brain tumor classification is a very challenging task in large spatial structural variability of the surrounding region of brain tumor. In this paper, we are provided with an overview of brain tumor detection using the deep learning Unet model. We used four types of Unet models 1. Unet model 2.ResUnet model 3. Resnext50Unet model 4. InceptionV3Unet model. The performance of the proposed model is measured and the result is compared with those of other approaches reported in literature. It is found that the proposed work is more efficacious than the state of art techniques.