An Optimized Level Set Method Based on QPSO and Fuzzy Clustering

• DOI: 10.1587/transinf.2018edp7132
• Publication Date: 2019-04-30T18:21:09Z
• Authors: Ling YANG; Yuanqi FU; Zhongke WANG; Xiaoqiong ZHEN; Zhipeng YANG; Xingang FAN
• Keywords: Initialization

A new fuzzy level set method (FLSM) based on the global search capability of quantum particle swarm optimization (QPSO) is proposed to improve stability and precision image segmentation, reduce sensitivity initialization. The combination QPSO-FLSM algorithm iteratively optimizes initial contours using QPSO c-means clustering, then utilizes (LSM) segment images. exploits obtain a stable cluster center pre-segmentation contour closer region interest during iteration. In implementation in segmenting liver tumors, brain tissues, lightning images, fitness function objective optimized by 10% comparison original FLSM algorithm. achieved from are also more than that FLSM. resulted improved final segmentation.