Brain Metastasis Tumor Detection using Image Segmentation and VGG16 Architecture

In recent years, brain tumors have risen to the position of top cause of mortality around the globe. A brain tumor is defined as abnormal cell growth in the brain. Tumors may be categorized into two broad categories: benign and cancerous tumors. The brain may develop cancerous tumors, and there are additional diseases known as brain metastasis tumors that spread from other places. The prompt detection and categorization of this tumor are critical, as they may reveal the probable diagnosis and treatment plan. In this research,Brain Metastasis Tumors are detected by building a model using VGG16 architecture. The kaggle brain tumor data collection is used for train and evaluate the models specified. As described in the study, the effectiveness of the designs is evaluated, and performance traits like Accuracy, Sensitivity, and Specificity are calculated and contrasted Alexnet and Googlenet.