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Computer Assisted Detection and Analysis of Tall Cell Variant Papillary Thyroid Carcinoma in Histological Images

机译:计算机辅助检测与分析高细胞变异乳头状甲状腺癌组织学图像

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The number of new cases of thyroid cancer are dramatically increasing as incidences of this cancer have more than doubled since the early 1970s. Tall cell variant (TCV-PTC) papillary thyroid carcinoma is one type of thyroid cancer that is more aggressive and usually associated with higher local recurrence and distant metastasis. This variant can be identified through visual characteristics of cells in histological images. Thus, we created a fully automatic algorithm that is able to segment cells using a multi-stage approach. Our method learns the statistical characteristics of nuclei and cells during the segmentation process and utilizes this information for a more accurate result. Furthermore, we are able to analyze the detected regions and extract characteristic cell data that can be used to assist in clinical diagnosis.
机译:由于自20世纪70年代初以来,这种癌症的发生率大于一倍以上,这种甲状腺癌的新病例的数量显着增加。高细胞变异(TCV-PTC)乳头状甲状腺癌是一种类型的甲状腺癌,更具侵袭性,通常与局部复发和远处转移相关。可以通过组织学图像中的细胞的视觉特征来识别该变体。因此,我们创建了一种全自动算法,可以使用多级方法进行分段单元。我们的方法在分割过程中学习核和细胞的统计特征,并利用这些信息进行更准确的结果。此外,我们能够分析检测到的区域并提取可用于有助于临床诊断的特征细胞数据。

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