Segmentation of Regions of Interest in Lung CT Images Based on 2-D OTSU Optimized by Genetic Algorithm
It is the key and difficult step to segment and extract suspected nodular lesions from CT images for lung cancer CAD system. A segmentation method is proposed based on 2-D OTSU optimized by genetic algorithm for Regions of Interest (ROI) in thoracic CT images in this paper. The chromosome is encoded in binaryzation by gray of original image, and the populations is produced randomly, then through operations of choice, cross and mutation, the optimum threshold value is obtained. 2-D OTSU combines information of spatial neighborhood pixels with the whole image gray value, so it can remove most of noise. Genetic algorithm is used to solve the optimum threshold, it can decrease the run time greatly. Experiment results indicated that the algorithm can extract ROIs in lung CT images effectively in consideration of the balance of efficiency and quality. The segmentation method based on 2-D OTSU optimized by genetic algorithm proposed in this paper is effective for extraction of ROI in CT images.
lung cancer CAD Region of Interest genetic algorithm 2-D OTSU optimization
Wei Ying Chang Cunxi Jia Tong Xu Xinhe
College of Information Science and Engineering,Northeastern University,Shenyang 110004
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
5185-5189
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）