A Review on the Role of Deep Learning for Brain Tumor Detection and Classification

Through the application of advanced deep-learning techniques, brain tumor detection and classification have advanced significantly in the last ten years in medical imaging. The purpose of this work is to study how deep learning models, namely convolutional neural network models, can improve the accuracy and speed of brain tumor diagnosis. Deep learning has been applied to analyze brain MRI data, and the results have been promising in terms of categorizing different types of brain tumors-a crucial component of comprehensive treatment plans. Large datasets of brain scans are used to train deep neural network models, which enable them to identify subtle patterns and traits that may be invisible to human observers. When compared to traditional methods, these models have the potential to produce faster diagnostic results, which would shorten the time patients must wait for a diagnosis.