Pemodelan Segmentasi Sel Epitel Serviks Pada Citra Digital PAP SMEAR

Komariyuli Anwariyah, Dedy Sofyan
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引用次数: 1

Abstract

Cervical cancer is a disease that is very deadly. The level of this disease in Indonesia is very high, the rate of prevalence in 2013 of about 0.8% with an estimated 92 692 absolute throughout Indonesia. Early detection of cancer can be done with a Pap cytology examination. Slide readings performed by a specialist in anatomical pathology where normal conditions at least there should be 8000-12000 cells in good condition. This reading is not easy and has some constraints, it is necessary to melakkan designed system capable of automatically reading slide. System automation is expected to reduce errors due to manual readings. One of the stages in the building automation system is the segmentation of the cell to separate the cells from background objects. Separation is done by implementing the method of minima and maxima region, as well as the implementation of a subset of the region area. From this study, it was found that the model is implemented showed that the implementation of the model can be used to do the segmentation process either cell cytoplasm and nucleus.
在 PAP SMEAR 数字图像中建立宫颈上皮细胞分割模型
子宫颈癌是一种非常致命的疾病。这种疾病在印度尼西亚的发病率非常高,2013年的患病率约为0.8%,印度尼西亚全国估计有92 692例绝对病例。早期发现癌症可以通过巴氏细胞学检查来完成。切片读数由解剖病理学专家进行,正常情况下至少应有8000-12000个细胞处于良好状态。这样读取不容易且有一定的限制,就有必要设计出能够自动读取幻灯片的系统。系统自动化有望减少由于手动读数造成的错误。建筑自动化系统的一个阶段是单元分割,将单元从背景对象中分离出来。分离是通过实现最小和最大区域的方法,以及实现区域面积的子集来实现的。从本研究中发现,该模型的实现表明,该模型的实现可以用于细胞质和细胞核的分割过程。
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