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A novel morphological segmentation method for evaluating estrogen receptors' status in breast tissue images

机译:一种评估乳房组织图像中雌激素受体状态的新型形态学分割方法

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In this paper, we propose a fully automated method able to perform accurate nuclear segmentation in immunohistochemical breast tissue images in order to provide quantitative assessment of estrogen receptor's status that will help pathologists in their diagnosis. The presented approach is based on color deconvolution and an enhanced morphological processing, which is used to identify positive stained nuclei and to separate all touching nuclei in the microscopic image for a subsequent cancer evaluation. Experiments on several breast cancer images of different patients admitted into the Tunisian Salah Azaiez Cancer Center, show the efficiency of the proposed method when compared to the manual evaluation of experts.
机译:在本文中,我们提出了一种能够在免疫组织化学乳腺组织图像中执行准确的核分割的全自动方法,以提供对雌激素受体状态的定量评估,这将有助于病理学家进行诊断。提出的方法基于颜色反卷积和增强的形态学处理,用于识别阳性染色的细胞核并分离显微图像中所有接触的细胞核,以用于随后的癌症评估。对突尼斯萨拉赫·阿扎伊兹癌症中心收治的不同患者的几幅乳腺癌图像进行的实验表明,与专家的人工评估相比,该方法的有效性。

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