液晶与显示Issue(6)：1000-1007,8.DOI:10.3788/YJYXS20153006.1000
基于粒子群优化的 Otsu 肺组织分割算法
Improved lung segmentation algorithm based on 2D Otsu optimized by PSO
摘要
Abstract
This paper develops an automatic segmentation method of lung image using two dimensional Otsu method based on particle swarm optimization in order to reduce operation time.Aiming at the shortage of the traditional two dimensional Otsu based on particle swarm optimization,which the cal-culating quantity is large and standard particle swarm algorithm is easy to fall into local optimum,an improved lung segmentation based on 2D Otsu optimized by PSO is proposed in this paper.Using the grayscale-gradient two-dimensional histogram,not only reduces the amount of histogram’s calcula-tion,but also narrows the searching area of particles.The algorithm uses the improved PSO which based on diversity of particle symmetrical distribution to search optimal threshold.In the process of algorithm,the region filling algorithm is used to remove background in order to make the threshold segmentation of lung better,and the morphology operations to remove noise and repair holes which in the target image.The threshold segmenting time in this algorithm is about 0.2 s,increased about 1 6% than the speed of the traditional Otsu threshold segmentation optimized by PSO,the size of the CT images is 5 12 × 5 12 pixels in this experiment.The segmentation algorithm in this paper can seg-ment the lung in CT image automatically,not only ensures the accuracy of the segmentation,but also improves the speed of the segmentation in comparison with conventional algorithms.关键词
二维 Otsu/改进粒子群/孔洞填充/形态学操作/肺组织自动分割Key words
two-dimensional Otsu/improved PSO/region filling/morphological operations/automatic lung segmentation分类
信息技术与安全科学引用本文复制引用
孟亚州,马瑜,白冰,高林爽..基于粒子群优化的 Otsu 肺组织分割算法[J].液晶与显示,2015,(6):1000-1007,8.基金项目
宁夏回族自治区2012年科技攻关计划项目(No.2012ZYG011) Supported by Key Science and Technology Program of Ningxia Hui Autonomous Region,China (No.2012ZYG011) （No.2012ZYG011）
