Glaser E M, McMullen N T
Anal Quant Cytol Histol. 1986 Jun;8(2):116-27.
Despite impressive advances in the application of computer image analysis to cytology, many of the identification tasks that cytologists are called on to perform remain refractory to automated image analysis. The major reason is that a large fraction of these images, though simple for a human to deal with, are too complex to yield to current image analysis methodologies. It may be years before automated computer image analysis is reduced to clinical practicality. Even then, it is not clear that all cytologic image analyses will prove amenable to automation. In the meantime, semiautomatic image analysis (computer-aided microscopy) can provide a viable alternative, especially to persistently difficult image analysis problems. In semiautomatic image analysis, the onerous tasks of data acquisition--e.g., stage movement, data entry and storage--are left to the computer, while the decision-making tasks-e.g., identifying a cell's morphologic class--are left to the observer. Such a system proves to be easy and flexible to use as well as economical to build. It can also provide a reliable data base for the later evaluation of fully automated systems as they are developed. One such semiautomatic system, the Image Combining Computer Microscope (ICCM), is described, and the range of its application is illustrated. Some of the examples of ICCM applications discussed are: neuronal cell plots, three-dimensional dendrite tracking, serial section reconstruction of axons and mapping of plaques and tangles in Alzheimer's disease. They illustrate how powerful a semiautomated system can be in handling complex image analysis problems. It is suggested that semiautomated image analysis provides a viable long-range alternative to many cytologic image analysis problems.
尽管计算机图像分析在细胞学应用方面取得了令人瞩目的进展,但细胞学家需要执行的许多识别任务仍难以通过自动图像分析完成。主要原因是这些图像中的很大一部分,虽然人类处理起来很简单,但对于当前的图像分析方法来说过于复杂。自动计算机图像分析可能需要数年时间才能应用于临床实际。即便如此,也不清楚所有的细胞学图像分析都能实现自动化。与此同时,半自动图像分析(计算机辅助显微镜检查)可以提供一个可行的替代方案,特别是对于一直难以解决的图像分析问题。在半自动图像分析中,繁重的数据采集任务,如载物台移动、数据录入和存储,由计算机完成,而决策任务,如识别细胞的形态类别,则由观察者完成。这样的系统使用起来简单灵活,构建成本也较低。它还可以为全自动系统开发后的后期评估提供可靠的数据库。本文描述了一种这样的半自动系统——图像组合计算机显微镜(ICCM),并说明了其应用范围。讨论的ICCM应用实例包括:神经元细胞绘图、三维树突追踪、轴突的连续切片重建以及阿尔茨海默病中斑块和缠结的映射。这些实例说明了半自动系统在处理复杂图像分析问题时的强大功能。有人认为,半自动图像分析为许多细胞学图像分析问题提供了一个可行的长期替代方案。