CentroidNet:一个轻量级，快速的核质心检测模型，用于乳房Ki67评分

Q3 Computer Science

中国图象图形学报 Pub Date : 2023-01-01 DOI:10.11834/jig.211207

Wen Ke, Jin Xu, An Hong, He Jie, Wang Jue

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引用次数: 0

摘要

目的乳腺癌预后Ki67评分可作为判断恶性(侵袭性)细胞增殖率的重要指标。阴性和阳性核检测是Ki67评分的重要组成部分。一种自动化的核检测算法可以减轻观察者内部或观察者之间的变化和劳动密集型核计数的负面影响。在

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CentroidNet：a light-weight，fast nuclei centroid detection model for breast Ki67 scoring

： Objective Breast cancer - prognostic Ki67 score can be as a key indicator for the proliferation rate of malignant （ invasive ） cells. Negative and positive nuclei detection is an essential part of Ki67 scoring. An automated algorithm for nuclei detection can alleviate the negative impact of intra/inter - observer variation and labor - intensive nuclei counting. In

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来源期刊

中国图象图形学报 Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

1.20

自引率

0.00%

发文量

6776