中国医疗设备2018，Vol.33Issue(6)：16-20,5.DOI:10.3969/j.issn.1674-1633.2018.06.004
基于改进的FCM模糊聚类的颅内出血 CT图像分割研究
Study on CT Image Segmentation of Intracranial Hemorrhage Based on Improved FCM Fuzzy Clustering
摘要
Abstract
In this paper, an improved fuzzy C-means (FCM) algorithm for the segmentation of intracranial hemorrhage lesions was proposed for the hemorrhagic lesions of human brain CT images. Firstly, the brain CT images were pre-divided, and the intracranial structures were extracted from the source CT images by left and right scanning algorithm and median filtering algorithm. Then the pre-segmentation intracranial structures were obtained by adding the objective function and membership function to the spatial information of improved FCM clustering algorithm for extraction of hemorrhagic lesions. Through CT brain images and CT brain images with salt and pepper noise segmentation, the results showed that the algorithm was insensitive to noise and can accurately segregate hemorrhagic lesions.关键词
颅脑CT/脑出血/出血病灶/空间信息/模糊C-均值/左右扫描算法Key words
brain CT/cerebral hemorrhage/hemorrhagic lesions/spatial information/fuzzy C-means/left and right scanning algorithm分类
医药卫生引用本文复制引用
姜春雨,刘景鑫,钟慧湘,李慧盈,李大军..基于改进的FCM模糊聚类的颅内出血 CT图像分割研究[J].中国医疗设备,2018,33(6):16-20,5.基金项目
国家重点研发计划(2016YFC0103500) （2016YFC0103500）
吉林省省校共建—战略性新兴产业培育项目(SXGJXX2017-5) （SXGJXX2017-5）
吉林大学高层次科技创新团队建设项目(2017TD-27). （2017TD-27）
