Enhanced Detection of Brain Tumors using Fusion-Based Feature Optimization and Stacking Ensemble Algorithm

The variation of the appearance of brain tumors is a challenging detection task-the interpretation of cells due to abnormal growth in dimension decreases the accuracy of the detection algorithm. Recently, several algorithms have been applied based on transform-based and machine learning to detect brain tumors. The mapping of retrieved brain tumor features in the classification algorithms is the main drawback of these techniques. This paper deployed a feature of a fusion-based approach for detecting brain tumours-the feature of a fusion approach using transform-based function and a heuristic-based algorithm. The fused feature passes through the proposed machine learning algorithm for detection-the proposed detection using a multi-kernel.