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Automated segmentation of Mitotic Cells for in vitro histological evaluation of oral squamous cell carcinoma

机译:用于口腔鳞状细胞癌体外组织学评价的有偶联细胞的自动分割

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In in vitro histological assessment, mitotic cells play one of the key roles for the diagnosis of oral squamous cell carcinoma (OSCC). In view of this, our paper aims to develop a computer assisted mitotic cell segmentation scheme for automated recognition from microscopic images of OSCC. The methodology includes multilevel thresholding, statistical moment features and classification and regression tree (CART) model. Performance of the proposed algorithm has also been evaluated.
机译:在体外组织学评估中,有丝分裂细胞在口腔鳞状细胞癌(OSCC)的诊断中发挥其中一个关键作用。鉴于此,我们的论文旨在开发一种计算机辅助有丝分细胞分段方案,用于从OSCC的微观图像自动识别。该方法包括多级阈值,统计时刻特征和分类和回归树(推车)模型。还评估了所提出的算法的性能。

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