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ASSESSING OF MITOTIC ACTIVITY BY IMAGE ANALYSIS

机译:通过图像分析评估有丝分裂活性

摘要

A method for the automated analysis of digital images, particularly for the purpose of assessing mitotic activity from images of histological slides for prognostication of breast cancer. The method includes the steps of identifying the locations of objects within the image which have intensity and size characteristics consistent with mitotic epithelial cell nuclei, taking the darkest 10 % of those objects, deriving contours indicating their boundary shape, and smoothing and measuring the curvature around the boundaries using a Probability Density Association Filter (PDAF). The PDAF output is used to compute a measure of any concavity of the boundary - a good indicator of mitosis. Objects are finally classified as representing mitotic nuclei or not, as a function of boundary concavity and mean intensity, by use of a Fisher classifier trained on known examples. Other uses for the method could include the analysis of images of soil samples containing certain types of seeds or other particles.
机译:一种用于自动分析数字图像的方法,特别是用于从组织学切片图像评估乳腺癌的有丝分裂活性的目的。该方法包括以下步骤:识别图像中具有与有丝分裂上皮细胞核一致的强度和大小特征的对象的位置,取这些对象中最暗的10%,得出指示其边界形状的轮廓,并对周围的曲率进行平滑和测量使用概率密度关联过滤器(PDAF)确定边界。 PDAF输出用于计算边界的任何凹度的度量-有丝分裂的良好指标。最后,通过使用在已知实例上训练的Fisher分类器,根据边界凹度和平均强度将对象分类为是否表示有丝分裂核。该方法的其他用途可能包括分析包含某些类型的种子或其他颗粒的土壤样品的图像。

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