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[关于通过电子光学表征和成功的含金属分泌颗粒自动图像分析来确定胰岛细胞功能活性的精确形态学指标的研究(作者译)]

[Investigations about ascertainment of exact morphological indices for the functionally activity of islets cells by means of electron optical characterizing and succeeded automatically image analysis of metal-containing secreting granules (author's transl)].

作者信息

Schmidt R, Meinel P, Schultka R

出版信息

Acta Histochem. 1977;58(1):100-4.

PMID:404820
Abstract

Biological image analysis with the "Quantimet 720" has been surrounded to date by difficulties due to the complexity of the image itself, and the difficulty of the Quantimet to discriminate between different objects on the basis of their grey levels alone (Bradbury 1975). Although the makers of image analysing computers try to diminish these difficulties by contructing new models of computers in future, we have the opinion, that it is possible to receive already today excellent results in image analysing of structures in biology and medicine under the following condition: selective staining of objects, we want to measure by simultaneous discriminating of those structures, which influence negatively the image analysing on the basis of their grey levels.

摘要

迄今为止,由于图像本身的复杂性以及Quantimet仅基于灰度级别区分不同物体的困难,使用“Quantimet 720”进行生物图像分析一直面临诸多困难(布拉德伯里,1975年)。尽管图像分析计算机的制造商试图通过在未来构建新的计算机模型来减少这些困难,但我们认为,在以下条件下,今天就有可能在生物学和医学结构的图像分析中获得出色的结果:对我们想要测量的物体进行选择性染色,同时区分那些基于灰度级别对图像分析产生负面影响的结构。

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