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An automatic system for cell nuclei pleomorphism segmentation in histopathological images of breast cancer

机译:乳腺癌组织病理学图像中细胞核渗透分割的自动系统

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Nuclear pleomorphism is one of the criteria for diagnosing and grading breast cancer. The grading that is made by pathologist is subjective and prone to inter, intra observer variations. Furthermore, pathologists may need a huge time for evaluating all cases per day. Therefore, there is a necessity to provide an automatic system for a better diagnosis and detection. This paper proposes an automatic system for detecting and segmenting cancerous nuclei, which is partly different from healthy nuclei segmentation systems. In contrast, our system detects critical nuclei with any shape, border and chromatin density even in higher scores. This system avoids segmenting healthy cell nuclei. It only detects and segments a high percentage of deformed cell nuclei, which are necessary for nuclear pleomorphism scoring even cells with vesicular nuclei that are not detected in any other algorithms.
机译:核渗透是诊断和分级乳腺癌的标准之一。 病理学家制造的分级是主观和容易互连,内部观察者变化。 此外,病理学家可能需要大量时间来评估每天的所有病例。 因此,必须提供一种用于更好的诊断和检测的自动系统。 本文提出了一种用于检测和分割癌细胞的自动系统,其部分与健康核细胞分段系统分成。 相比之下,即使在较高的分数中,我们的系统也以任何形状,边界和染色质密度检测关键核。 该系统避免了分段健康的细胞核。 它只检测和区段高百分比的变形细胞核,这对于核渗透性均匀的甚至具有在任何其他算法中未检测到的凹形细胞核的细胞所必需的。

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