Muhammad Ali1, Jamal Hussain Shah1, Muhammad Attique Khan2, Majed Alhaisoni3, Usman Tariq4, Tallha Akram5, Ye Jin Kim6, Byoungchol Chang7,*
CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4501-4518, 2022, DOI:10.32604/cmc.2022.030392
Abstract Tumor detection has been an active research topic in recent years due to the high mortality rate. Computer vision (CV) and image processing techniques have recently become popular for detecting tumors in MRI images. The automated detection process is simpler and takes less time than manual processing. In addition, the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for clinicians. We proposed a new framework for tumor detection as well as tumor classification into relevant categories in this paper. For tumor segmentation, the proposed framework employs the Particle Swarm Optimization (PSO) algorithm, and for… More >