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AUTOMATIC ABNORMAL CELL RECOGNITION METHOD BASED ON IMAGE SPLICING

机译:基于图像拼接的自动异常细胞识别方法

摘要

An automatic abnormal cell recognition method, the method including: 1) scanning a slide using a digital pathological scanner and obtaining a cytological slide image; 2) obtaining a set of centroid coordinates of all nuclei that is denoted as CentroidOfNucleus by automatically localizing nuclei of all cells in the cytological slide image using a feature fusion based localizing method; 3) obtaining a set of cell square region of interest (ROI) images that are denoted as ROI_images,; 4) grouping all cell images in the ROI_images into different groups based on sampling without replacement, where each group contains ROW×COLUMN cell images with preset ROW and COLUMN parameters; obtaining a set of splice images; and 5) classifying all cell images in the splice image simultaneously by using the splice image as an input of a trained deep neural network; and recognizing cells classified as abnormal categories.
机译:自动异常电池识别方法,包括:1)使用数字病理扫描仪扫描载玻片并获得细胞学幻灯片图像; 2)通过使用基于特征融合的定位方法自动定位细胞学滑块中的所有细胞的核来获得所有核的一组质心坐标。 3)获取一组感兴趣的小区平方区域(ROI)图像,其表示为ROI_IMAGES; 4)将ROI_IMAGE中的所有单元格图像基于采样对不同的组,无需更换,其中每个组包含具有预设行和列参数的行×列单元格;获得一组拼接图像; 5)通过使用拼接图像作为训练的深神经网络的输入,同时对接头图像中的所有单元图像进行分类;并识别分类为异常类别的细胞。

著录项

  • 公开/公告号US2021065367A1

    专利类型

  • 公开/公告日2021-03-04

    原文格式PDF

  • 申请/专利权人 WUHAN UNIVERSITY;

    申请/专利号US202017002751

  • 申请日2020-08-25

  • 分类号G06T7;G06T3/40;

  • 国家 US

  • 入库时间 2022-08-24 17:29:50

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