An Inception V3 Based Glioma Brain Tumor Detection in MRI Images

Detecting brain tumors presents several significant challenges, MRI and CT scans, while advanced, still have limitations in resolution, making it difficult to detect very small tumors or differentiate between tumor types. Developing effective AI models requires large amounts of high-quality annotated data, which can be difficult to obtain. Machine learning models, particularly deep learning, can be complex and their decision-making process can be opaque, making it hard for clinicians to trust and validate their outputs. To overcome the limitations, In this research modified Inception V3algorithm used to detect and classify the brain tumor from the MRI images. Mendeley Brain Tumor dataset with 600 images taken. These images divided into two groups namely glioma and notumor. Essential features extracted by the proposed classifier, which enable to provide enhanced accuracy in detection of glioma compare to the conventional methods.