Brain Tumor Detection and Classification
Author(s): K. Neela Mohan Reddy, C. Veena, V. Narendra, D. Rajesh, S. Mounika
Publication #: 2504049
Date of Publication: 16.04.2025
Country: India
Pages: 1-10
Published In: Volume 11 Issue 2 April-2025
Abstract
One of the main causes of cancer-related deaths globally is brain tumors. The lack of an effective screening technique to identify high-risk patients and the fact that cancer-specific symptoms only appear at an advanced stage make it difficult to diagnose brain cancer early. However, if caught early enough, brain cancer can be healed. The goal of this effort is to identify brain tumors from CT scans. To find the tumor, it employs CNN Model Architecture and image processing methods. The CNN Model Architecture is used to identify the tumorous region in the picture after it has been pre-processed. The goal is to improve the model parameters in order to lower the classification error on the training set. Furthermore, our CNN model also shows the capacity to forecast the stage of a brain tumor by utilizing fine-tuning approaches like regularization and hyper parameter optimization.
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