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A Method for Identification and Visualization of Histological Image Structures Relevant to the Cancer Patient Conditions

机译:一种识别和可视化与癌症患者状况相关的组织学图像结构的方法

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A method is suggested for identification and visualization of histology image structures relevant to the key characteristics of the state of cancer patients. The method is based on a multi-step procedure which includes calculating image descriptors, extracting their principal components, correlating them to known object properties and mapping disclosed regularities all the way back up to the corresponding image structures they found to be linked with. Image descriptors employed are extended 4D color co-occurrence matrices counting the occurrence of all possible pixel triplets located at the vertices of equilateral triangles of different size. The method is demonstrated on a sample of 952 histology images taken from 68 women with clinically confirmed diagnosis of ovarian cancer. As a result, a number of associations between the patients' conditions and morphological image structures were found including both easily explainable and the ones whose biological substrate remains obscured.
机译:建议一种方法来识别和可视化与癌症患者状态的关键特征有关的组织学图像结构。该方法基于多步骤过程,该过程包括计算图像描述符,提取它们的主要成分,将它们与已知的对象属性相关联以及将公开的规则映射到所有与之关联的对应图像结构。所采用的图像描述符是扩展的4D颜色共现矩阵,该矩阵对出现在不同大小的等边三角形的顶点处的所有可能的像素三元组进行计数。该方法在从68位经临床确认诊断为卵巢癌的女性中采集的952个组织学图像样本中得到了证明。结果,发现了患者状况和形态图像结构之间的许多关联,包括容易解释的和生物学底物仍然被遮盖的关联。

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