부산대학교 도서관

Soft computing is a developing field in the modern era of diagnostic aid. Multilevel thresholding is employed in this study to segment actual liver CT scan images. To segment, an image that is helpful in the detection of a liver cyst, a modified fuzzy c-means clustering (MFCMC) and modified whale optimization algorithm (MWOA) are implemented. At an optimal number of thresholds, 2, 3, 4, and 5, multilevel thresholding is carried out. Results from several optimization algorithms, including Particle Swarm optimization, BAT, Differential Evolution, and clustering algorithm K mean clustering, are compared to the proposed approach’s performance. The MFCMC & MWOA method offers precise visual outcomes in addition to being effective in metric-based Uniformity, Peak signal-to-noise ratio (PSNR) and Root Mean Square (RMS) Error values. Findings indicate that, in contrast to other algorithms, the proposed approach finds the best number of threshold values more rapidly.