Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and EfficientNet

Accurate and timely diagnosis of brain tumors is critical for successful treatment of the disease. Early detection not only aids in the development of better medication, but it can also save a life in the long run. The domain of brain tumor analysis has efficiently applied medical image processing ideas, particularly on MR images. This paper presents segmentation using Convolutional Neural Networks (CNN) architecture with ResNet50 and EfficientNet as backbones on the Figshare data set, with an accuracy level of 0.xxx.