肝癌病理切片瘤巨细胞和核分裂象定量评估方法与设备
By using deep learning methods to quantitatively assess giant tumor cells and mitotic figures in liver cancer pathological sections, the problem of low efficiency in interpreting cell-level feature structures in liver cancer pathological section images was solved. This enabled rapid and accurate detection and counting, improving the accuracy and efficiency of pathological diagnosis and quantifying the relationship between cell-level feature structures and survival.
CN118469924BActive Publication Date: 2026-07-17TSINGHUA SHENZHEN INTERNATIONAL GRADUATE SCHOOL
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TSINGHUA SHENZHEN INTERNATIONAL GRADUATE SCHOOL
- Filing Date
- 2024-04-30
- Publication Date
- 2026-07-17
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Figure CN118469924B_ABST
Abstract
本发明公开了一种肝癌病理切片瘤巨细胞和核分裂象定量评估方法及设备，该方法包括如下步骤：S1：读取肝癌病理切片数据集中的病理图像，对所述病理图像进行组织前景分割得到组织区域掩膜；S2：将所述组织区域掩膜对应的组织区域裁剪成图块后进行推理，区分所述图块中的肿瘤图块与非肿瘤图块，并对所述肿瘤图块进行定位；S3：针对所述肿瘤图块，对瘤巨细胞和核分裂象进行定量评估和计数，得到全定量结果，并生成全片细胞级特征结构热图。本方法可自动对瘤巨细胞和核分裂象进行快速精准检测和计数。
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