Brain Tumour Detection by Multilevel Thresholding Using Opposition Equilibrium Optimizer

Abstract

The detection of the exact location of a tumour in a complex brain structure is one of the emerging fields of a medical image segmentation study. The ability to segment tumours from magnetic resonance imaging (MRI) brain pictures is crucial for providing effective treatment and surgical planning. Radiologists also accept the importance of the optimised result of multilevel thresholding for segmenting the desired region from the medical images. The use of entropy-based multilevel thresholding with the opposition equilibrium optimizer (OEO) to segment MRI images of the brain into the distinct regions including the tumour is presented in this paper. Finally, the region growing method is used to isolate the complete tumour part. Furthermore, the suggested method is tested on the BRATS 2018 segmentation Challenge dataset, demonstrating its efficacy with better and acceptable Precision, Jaccard index, and dice coefficient values. As a result, the proposed segmentation method is therapeutically relevant.