三维医学图像分割标注技术的回顾  

Review:Segmentation and Classification Methods of 3D Medical Images

作　　者：谭鸥[1] 段会龙[1] 吕维雪[1] 

机构地区：[1]浙江大学生物医学工程与仪器科学学院,浙江杭州310027

出　　处：《中国医疗器械杂志》2002年第3期197-206,共10页Chinese Journal of Medical Instrumentation

摘　　要：综述20世纪90年代以来三维医学图象分割标注技术。从方法学的观点将现有方法分为以下几类:聚类（阈值）;统计学方法;变形轮廓线;区域生长;数学形态学;非线性方法（模糊分割,神经网络,遗传算法）;三维模型。对各种类型逐一进行了细分,并给出了详细的例子。最后,论文还对三维医学图像分割标注的发展趋势进行了评述。This paper presents a survey of recent publications(published in 1990 or later) concerning segmentation and classification of medical images. These methods will be classified into six types: cluster (threshold), statistics methods, deformable contour, region growing, mathematics morphology, nonlinear methods (fuzzy segmentation, neural networks,genetic algorithm)and 3D model. Each of the major classes of image segmentation and classification techniques and several specific examples of each class of algorithm are described respectively in detail. At last,the developing trend of 3D medical image is also discussed.

关 键 词：三维医学图像分割标注技术 三维医学图像 图像分割 图像标注 

分 类 号：R318.6[医药卫生—生物医学工程]