Precise Identification and Segmentation of Anomalies in MR Brain Images Using Emperor Penguin Optimization Based Weighted Fuzzy C-Means Clustering

In numerous applications, segmentation of images is essential to image comprehension, extraction of features, evaluation, and understanding. It is widely used in healthcare for a variety of purposes, including tissue categorization, tumor location identification, tumor size calculation, blood cell separation, preparation for surgery, atlas comparison, and registration of images. One of the widely used algorithms for clustering in segmentation of medical images is fuzzy c-means (FCM). However, FCM is extremely susceptible to noise since it ignores spatial information when segmenting images. The limitations of FCM might be overcome by adding weighted FCM, which takes into account the spatial and intensity information of the surrounding pixels in this situation. A population-centered meta-heuristic technique called Emperor Penguin Optimizer (EPO) was created currently to mimic the huddling manners of emperor penguins. Regarding how well EPO performs when handling universal issues with optimization, different outcomes were noted. In order to achieve an appropriate equilibrium among exploration and exploitation, two variables belonging to the EPO must be adjusted. The EPO uses the emperor penguins to symbolize the potential solution, the huddle to signify the area of search, which is a two-dimensional L-shaped polygon plane, and the viable option to be represented by the emperor penguins arranged arbitrary. Determining the efficient mover that embodies the global best option among all the emperor penguins. The fact that EPO has been successfully applied to a wide variety of optimization problems has allowed it to gradually gather energy up to this point. It is suggested that EPO and WFCM be integrated to recognize and separate the abnormalities seen in brain magnetic resonance imaging (MRI). The effectiveness of the algorithm that has been established is confirmed through contrasting the dissection results with the corresponding ground truth images and by looking at specific performance metrics. The EPO-WFCM technique may assist doctors quickly identify tumors, that may result in a quicker treatment through improved care or planning for surgery.