Distribution error in quantitative digital image analysis systems and its correction algorithm

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Pub Date : 1988-11-01 DOI:10.1109/IEMBS.1988.94558

H.S. Choi, R. Dilley, Y. Kim, S. M. Schwartz

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引用次数: 1

Abstract

One of the major sources of the coefficient of variation in quantitative digital image analysis systems is the distribution error. It is caused by uneven optical density distribution within the measuring area. In digital image analysis systems, the measuring area is an individual pixel. The distribution error would be eliminated if we could measure the average optical density within the measuring area. However, most cameras used with light microscopes measure the average transmittance of a pixel. The image analysis system then converts the measured transmittance into an optical density. If the optical density distribution within a pixel is not uniform, the average optical density converted from the measured transmittance is different from the true optical density of the pixel. The authors call this conversional distribution error (CDE). They have analyzed and characterized this error, and developed an algorithm to minimize CDE by estimating the optical density distribution within a pixel.<>

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定量数字图像分析系统中的分布误差及其校正算法

定量数字图像分析系统中变异系数的主要来源之一是分布误差。这是由于测量区域内光密度分布不均匀造成的。在数字图像分析系统中，测量区域是一个单独的像素。如果能在测量区域内测量平均光密度，就可以消除分布误差。然而，大多数与光学显微镜一起使用的相机测量的是一个像素的平均透射率。然后，图像分析系统将测量到的透射率转换成光密度。如果像素内的光密度分布不均匀，则由测量透射率转换成的平均光密度与像素的真实光密度不一致。作者称之为转换分布误差(CDE)。他们分析并描述了这种误差，并开发了一种算法，通过估计像素内的光密度分布来最小化CDE。

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Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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