Feature quantification and abnormal detection on cervical squamous epithelial cells.
Feature quantification and abnormal detection on cervical squamous epithelial cells.
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DOI：
10.1155/2015/941680
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发表时间：
2015
影响因子：
--
通讯作者：
Zhang J
中科院分区：
文献类型：
--
作者：
Zhao M;Chen L;Bian L;Zhang J;Yao C;Zhang J
病理分析图像中异常细胞的特征分析和分类检测是实现计算机辅助疾病诊断的重要问题。本文研究了一种宫颈鳞状上皮细胞的提取方法。在宫颈细胞学分类标准和专家诊断经验的基础上，根据宫颈鳞片上皮细胞的形态、颜色和纹理特征提取表达描述子。此外，还得到了与细胞病理学相关的定量描述符，包括形态差异程度、细胞过度角化和深度染色程度。通过这些描述符可以建立量化值与病理特征之间的关系。最后，提出了一种基于特征量化的异常细胞检测方法。结合临床经验，该方法可以实现异常细胞的快速检测和细胞的初步分类。
Feature analysis and classification detection of abnormal cells from images for pathological analysis are an important issue for the realization of computer assisted disease diagnosis. This paper studies a method for cervical squamous epithelial cells. Based on cervical cytological classification standard and expert diagnostic experience, expressive descriptors are extracted according to morphology, color, and texture features of cervical scales epithelial cells. Further, quantificational descriptors related to cytopathology are derived as well, including morphological difference degree, cell hyperkeratosis, and deeply stained degree. The relationship between quantified value and pathological feature can be established by these descriptors. Finally, an effective method is proposed for detecting abnormal cells based on feature quantification. Integrated with clinical experience, the method can realize fast abnormal cell detection and preliminary cell classification.