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Development of Image Processing Algorithm for Cytological Diagnosis of Uterine Cervical Cancer Tissue Examination

机译:子宫宫颈癌组织检查细胞学诊断图像处理算法

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In this study is relevant to cell area extraction for cytological diagnosis of liquid-based cell examination being used for early diagnosis of uterine cervical cancer by utilizing image processing. As existing cytological diagnosis process has been performed manually by cytotechnologist, the amount of cell image that could be processed was limited. Therefore, in this study, cellular domain extraction through which automatic processing of cytological diagnosis process is enabled was performed and its condition was established depending on the size of cell nucleus based on cytological diagnosis standard of uterine cervical cancer cell. Obtained cell image was processed by hough transform matching with cell image by using matlab through preprocessing phase. As a result, 28 sample images among total 30 sample images were succeeded in finding out target cell and two sample images failed to find it. In the future, modification and verification for such failure case may be required to be performed. It is expected that the result of this study could be utilized for diagnosis process automation of liquid-based cell examination.
机译:本研究与细胞区域提取相关用于通过利用图像处理来用于早期诊断子宫宫颈癌的细胞学诊断。由于现有的细胞学诊断过程通过细胞技术学家手动进行,因此可以处理的细胞图像的量受到限制。因此,在该研究中,进行了细胞结构域提取,通过该细胞结构域提取通过其使能细胞学诊断过程的自动处理,并根据基于子宫宫颈癌细胞的细胞核的细胞核的尺寸来建立其条件。通过使用PATLAB通过预处理阶段通过Hough变换与细胞图像匹配来处理获得的细胞图像。结果,在发现目标单元中成功完成了28个样本图像,并在发现目标单元格中​​,两个样本图像未能找到它。在未来,可能需要进行对这种故障情况的修改和验证。预计本研究的结果可用于诊断基于液体细胞检查的过程自动化。

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