Advancing multi-categorization and segmentation in brain tumors using novel efficient deep learning approaches

Finally, a novel LWIFCM_CSA approach is introduced, which is the ensemble of Local-information weighted intuitionistic Fuzzy C-means clustering algorithm (LWIFCM) and Chameleon Swarm Algorithm (CSA). Conditional Tabular Generative Adversarial Network (CTGAN) is used to tackle class imbalance problems. While differentiating from existing approaches, the proposed approach gains a greater solution. This stable improvement in accuracy highlights the suggested classifier's strong performance and raises the possibility of more precise and trustworthy brain tumor classification. In addition, our method's processing time, which averaged 0.11 s, was significantly faster than that of previous approaches.