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Pilot Study of an Open-source Image Analysis Software for Automated Screening of Conventional Cervical Smears

机译:常规宫颈涂片自动筛查的开源图像分析软件的初步研究

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Introduction: The Pap stained cervical smear is a screening tool for cervical cancer. Commercial systems are used for automated screening of liquid based cervical smears. However, there is no image analysis software used for conventional cervical smears. The aim of this study was to develop and test the diagnostic accuracy of a software for analysis of conventional smears. Materials and Methods: The software was developed using Python programming language and open source libraries. It was standardized with images from Bethesda Interobserver Reproducibility Project. One hundred and thirty images from smears which were reported Negative for Intraepithelial Lesion or Malignancy (NILM), and 45 images where some abnormality has been reported, were collected from the archives of the hospital. The software was then tested on the images. Results: The software was able to segregate images based on overall nuclear: cytoplasmic ratio, coefficient of variation (CV) in nuclear size, nuclear membrane irregularity, and clustering. 68.88% of abnormal images were flagged by the software, as well as 19.23% of NILM images. The major difficulties faced were segmentation of overlapping cell clusters and separation of neutrophils. Conclusion: The software shows potential as a screening tool for conventional cervical smears; however, further refinement in technique is required.
机译:简介:Pap染色的宫颈涂片是宫颈癌的筛查工具。商业系统用于对液体基宫颈涂片进行自动筛选。但是,没有用于常规宫颈涂片的图像分析软件。这项研究的目的是开发和测试用于分析常规涂片的软件的诊断准确性。材料和方法:该软件是使用Python编程语言和开放源代码库开发的。它使用来自Bethesda Interobserver Reproducibility Project的图像进行了标准化。从医院档案中收集了一百三十张涂片报告为阴性的上皮内病变或恶性肿瘤(NILM)的图像,以及四十五张已报告异常的图像。然后在图像上测试了该软件。结果:该软件能够基于总体核:细胞质比率,核大小变异系数(CV),核膜不规则性和聚类来分离图像。该软件标记了68.88%的异常图像,以及19.23%的NILM图像。面临的主要困难是重叠细胞团的分割和嗜中性粒细胞的分离。结论:该软件显示了作为常规宫颈涂片筛查工具的潜力。但是,需要进一步完善技术。

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