Intelligent Multigrade Brain Tumor Identification in MRI: A Metaheuristic-Based Uncertain Set Framework
Saravanan Alagarsamy, Vishnuvarthanan Govindaraj, A. Shahina, D. Nagarajan
Abstract
This research intends to address the critical need for precise brain tumor prediction through the development of an automated method that entwines the Firefly (FF) algorithm and the interval type-II fuzzy (IT2FLS) technique. The proposed method improves tumor delineation in complex brain tissue by using the FF algorithm to find possible cluster positions and the IT2FLS system for final clustering. This algorithm demonstrates its versatility by processing diverse image sequences from BRATS challenge datasets (2017, 2018, and 2020), which encompass varying levels of complexity. Through comprehensive evaluation metrics such as sensitivity, specificity, and dice-overlap index (DOI), the proposed algorithm consistently yields improved segmentation results. Ultimately, this research aims to augment oncologists' perceptual acumen, facilitating enhanced intuition and comprehension of patients' conditions, thereby advancing decision-making capabilities in medical research.