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Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach

机译:在DLBCL组织样本中自动进行巨噬细胞计数:基于ROF过滤器的方法

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摘要

BackgroundFor analysis of the tumor microenvironment in diffuse large B-cell lymphoma (DLBCL) tissue samples, it is desirable to obtain information about counts and distribution of different macrophage subtypes. Until now, macrophage counts are mostly inferred from gene expression analysis of whole tissue sections, providing only indirect information. Direct analysis of immunohistochemically (IHC) fluorescence stained tissue samples is confronted with several difficulties, e.g. high variability of shape and size of target macrophages and strongly inhomogeneous intensity of staining. Consequently, application of commercial software is largely restricted to very rough analysis modes, and most macrophage counts are still obtained by manual counting in microarrays or high power fields, thus failing to represent the heterogeneity of tumor microenvironment adequately.
机译:背景为了分析弥漫性大B细胞淋巴瘤(DLBCL)组织样本中的肿瘤微环境,希望获得有关不同巨噬细胞亚型的计数和分布的信息。到目前为止,巨噬细胞计数主要是从整个组织切片的基因表达分析中推断出来的,仅提供间接信息。免疫组织化学(IHC)荧光染色的组织样品的直接分析面临许多困难,例如目标巨噬细胞的形状和大小的高度可变性以及强烈的染色强度不均一性。因此,商业软件的应用在很大程度上仅限于非常粗糙的分析模式,并且大多数巨噬细胞计数仍是通过在微阵列或高功率场中进行手动计数获得的,因此不能充分代表肿瘤微环境的异质性。

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