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首页> 外文期刊>Image Analysis & Stereology >TESTING HISTOLOGICAL IMAGES OF MAMMARY TISSUES ON COMPATIBILITY WITH THE BOOLEAN MODEL OF RANDOM SETS
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TESTING HISTOLOGICAL IMAGES OF MAMMARY TISSUES ON COMPATIBILITY WITH THE BOOLEAN MODEL OF RANDOM SETS

机译：使用随机集的布尔模型对哺乳动物组织的组织学图像进行兼容性测试

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摘要

Methods for testing the Boolean model assumption from binary images are briefly reviewed. Two hundred binary images of mammary cancer tissue and 200 images of mastopathic tissue were tested individually on the Boolean model assumption. In a previous paper, it had been found that a Monte Carlo method based on the approximation of the envelopes by a multi-normal distribution with the normalized intrinsic volume densities of parallel sets as a summary statistics had the highest power for this purpose. Hence, this method was used here as its first application to real biomedical data. It was found that mastopathic tissue deviates from the Boolean model significantly more strongly than mammary cancer tissue does.
机译：简要回顾了从二进制图像测试布尔模型假设的方法。在布尔模型假设下，分别测试了200个乳腺癌组织的二值图像和200个乳癌组织的图像。在以前的论文中，已经发现基于蒙特普罗方法的多正态分布逼近包络，并使用归一化并行组的归一化内在体积密度作为汇总统计量，此方法具有最高的功效。因此，此方法在这里首次用于实际的生物医学数据。发现乳腺病组织比乳癌组织明显更强地偏离布尔模型。

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