生物细胞图像分割技术的进展  

The State and Development of Cell Image Segmentation Technology

作　　者：马义德[1] 戴若兰[1] 李廉[2] 吴承虎[2] 

机构地区：[1]兰州大学干旱生态国家重点实验室,兰州730000 [2]兰州大学信息科学与工程学院,兰州730000

出　　处：《生物医学工程学杂志》2002年第3期487-492,共6页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目 ( 39770 375 );甘肃省自然科学基金资助项目 ( ZS0 0 1-A2 5 -0 0 8-Z)

摘　　要：阐述了小波变换、遗传算法、模糊数学、神经网络、数学形态学等生物细胞图像分割算法以及边缘检测、区域分割等传统图像分割算法为主的生物细胞图像分割技术的发展现状 ,指明了生物细胞图像本身具有的复杂性、多样性、各自差异性等属性是实现生物细胞图像全自动分割的难点 ,只有彻底结合生物视觉特性数学模型算法的研究和应用 。This paper describes the state and the development of the application of the modern and traditional image segmentation technology in cell slice image segmentation. It includes edge detection?regional segmentation?wavelet transform?fuzzy mathematics? artificial neural networks?morphological image segmentation and so on. At last, the paper summaries that it is difficult to generally segmentate any kind of biological cell slice image automatically because of the complex structure of cell and cell slice image is not even gray distributed. It should be pointed out that general automatic cell slice image segmentation will be achieved only if visual mathematics model corresponding to mammalian vision systems is setup entirely.

关 键 词：生物细胞 图像分割 小波变换 模糊数学 神经网络 

分 类 号：R-39[医药卫生]