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首页> 外文期刊>Computers in Biology and Medicine >The proportionator: unbiased stereological estimation using biased automatic image analysis and non-uniform probability proportional to size sampling.
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The proportionator: unbiased stereological estimation using biased automatic image analysis and non-uniform probability proportional to size sampling.

机译:比例器:使用有偏自动图像分析的无偏立体估计和与大小采样成比例的不均匀概率。

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摘要

The proportionator is a novel and radically different approach to sampling with microscopes based on the well-known statistical theory (probability proportional to size-PPS sampling). It uses automatic image analysis, with a large range of options, to assign to every field of view in the section a weight proportional to some characteristic of the structure under study. A typical and very simple example, examined here, is the amount of color characteristic for the structure, marked with a stain with known properties. The color may be specific or not. In the recorded list of weights in all fields, the desired number of fields is sampled automatically with probability proportional to the weight and presented to the expert observer. Using any known stereological probe and estimator, the correct count in these fields leads to a simple, unbiased estimate of the total amount of structure in the sections examined, which in turn leads to any of the known stereological estimates including size distributions and spatial distributions. The unbiasedness is not a function of the assumed relation between the weight and the structure, which is in practice always a biased relation from a stereological (integral geometric) point of view. The efficiency of the proportionator depends, however, directly on this relation to be positive. The sampling and estimation procedure is simulated in sections with characteristics and various kinds of noises in possibly realistic ranges. In all cases examined, the proportionator is 2-15-fold more efficient than the common systematic, uniformly random sampling. The simulations also indicate that the lack of a simple predictor of the coefficient of error (CE) due to field-to-field variation is a more severe problem for uniform sampling strategies than anticipated. Because of its entirely different sampling strategy, based on known but non-uniform sampling probabilities, the proportionator for the first time allows the real CE at the section level to be automatically estimated (not just predicted), unbiased-for all estimators and at no extra cost to the user.
机译:比例器是一种新颖的方法,它基于众所周知的统计理论(概率与大小PPS采样成比例)在显微镜下进行采样。它使用自动图像分析以及多种选择,为截面中的每个视野分配与所研究结构的某些特征成比例的权重。在此检查的一个典型且非常简单的示例是该结构的颜色特征量,该特征以带有已知特性的污渍标记。颜色可以是特定的,也可以不是。在记录的所有字段的权重列表中,以与权重成正比的概率自动采样所需的字段数,并提供给专家观察员。使用任何已知的立体探测和估计器,在这些字段中进行正确的计数都可以对检查区域中的结构总量进行简单,无偏的估计,从而可以得出任何已知的立体估计,包括大小分布和空间分布。无偏不是重量与结构之间假定关系的函数,实际上,从立体学(整体几何学)角度来看,无偏关系始终是有偏关系。但是,配比器的效率直接取决于这种关系是否为正。采样和估计过程在具有可能存在的现实范围内的特征和各种噪声的部分中进行了模拟。在所有检查的情况下,配比器的效率都比普通的系统化,均匀随机采样高2-15倍。模拟还表明,由于场间差异而导致缺乏简单的误差系数(CE)预测因子,对于统一采样策略而言,其问题比预期的更为严重。由于其完全不同的采样策略,基于已知但不均匀的采样概率,配比器首次允许自动估计(不仅是预测的)断面级别的真实CE,而不会为所有估计器带来偏见给用户带来额外的费用。

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