Fuzzy Refinement-Based Tissue and Ring Connectivity for Brain Skull Segmentation

Magnetic Resonance Imaging (MRI) based brain cancer segmentation methods need the skull stripping algorithms as their pre-processing tool. Skull is challenged by less accuracy and high time consumption; hence, an effective method needed for medical world. In this research, a novel on MRI proposed, which named 'Skull Stripping in using FHECE enhancement, Fuzzy clustering Morphological operations (SS_FFM)'. The contribution of paper 'Fusion Histogram equalization Edge-based Contrast Enhancement (FHECE)'. proposed SS_FFM essentially segments tissue region from background MRI. enhances approach weighted fusion Adaptive Equalization (AHE) edge-based contrast enhancement. also empowered new concept, integrated component three binary clustered outputs along with 'Tissue ring connectivity detection'. main advantage independent against connectivity' characteristic. Segmentation Accuracy (SA) analysis reveals that SA 1.39% compared to second-best method. reduces consumption 46.19% secondbest SS-UNET Experimental results terms F Score prove extended efficiency Hence, it can be used tool practitioners.