中国医疗设备2012，Vol.27Issue(9)：38-41,4.DOI:10.3969/j.issn.1674-1633.2012.09.007
FCM和Level Set在医学影像分割中的应用
Application of FCM and Level Set in Medical Image Segmentation
摘要
Abstract
Objective To explore RGAC-M (Region Based Geometric Active Contour-Model), in order to divide medical images more accurately. Methods By analyzing the existing defects of RGAC in medical image segmentation and improving its areas, RGAC-M is put forward, namely, by adopting many ways of substate initialization, reduces the sensibility of arithmetic to initial conditions, and meanwhile decreases manual intervention. Results In the way of various of brain (cinerea, alba, cerebrospinal fiuid, background and so on) segmentation, RGAC-M got good result. Conclusion RGAC-M could reduce iterations of image segmentation and improve segmentation speed and image quality.关键词
核磁共振成像/图像分割/模糊聚类/几何活动轮廓模型Key words
magnetic resonance imaging/ image segmentation/ fuzzy clustering/ geometric active contour分类
信息技术与安全科学引用本文复制引用
伍强,陈赛明,涂蓉..FCM和Level Set在医学影像分割中的应用[J].中国医疗设备,2012,27(9):38-41,4.基金项目
海南省自然科学基金项目(310154)资助. （310154）
