Brain Tumor Detection Using Machine Learning Hybrid Approach

The most aggressive, destructive, and lethal diseases, brain tumors (BTs) reduce patients' average life expectancy. Patients with BTs have a lower likelihood of survival when they receive inadequate medical care and a misdiagnosis. Magnetic resonance imaging (MRI) is frequently used for tumor analysis, where, the volume of data generated by MRI makes it challenging to manually segment images in a fair amount of time, which restricts the use of established standard clinical practice. Therefore, effective and automatic segmentation methods are needed. In recognizing various categories of brain tumors, the planned model accomplished improved version than other models. Compared to existing techniques, it also gave more specific and distinguishing information and accurate geography for brain tumor diagnosis.