Paper Key : IRJ************381
Author: Koppisetti Gowthami
Date Published: 09 Jul 2024
Abstract
Nowadays, tumors are the second leading cause of cancer, putting many patients at risk. The medical field urgently needs fast, automated, efficient, and reliable techniques to detect tumors, especially brain tumors, as early detection is crucial for effective treatment. Tumors are excess cells growing uncontrollably, depriving healthy cells of nutrients and leading to brain failure. Currently, doctors manually examine MR images to locate brain tumors, a process that is time-consuming and often inaccurate. By using Deep Learning architectures like Convolutional Neural Networks (CNN), we can improve brain tumor detection. This model predicts whether a tumor is present in an image, and if so, classifies it as one of three types: Glioma, Meningioma, or Pituitary tumor. If no tumor is detected, the model returns 'no tumor'. This approach enables doctors to provide proper treatment and save more patients.
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