The Method of Segmentation of Cervical Nuclei in Complex Background
Automatic screening technology developed in recent years. It applies image processing, and first recognizes nucleus and then measures the DNA contents accurately, so it can provide auxiliary for a doctor′s diagnosis. Image segmentation is the key technique of automatic screening system which directl...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2019-06-01
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| Series: | Journal of Harbin University of Science and Technology |
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| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1677 |
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| _version_ | 1849341094751371264 |
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| author | ZHAO Jing LIANG Long-kai HE Yong-jun XIE Yi-ning |
| author_facet | ZHAO Jing LIANG Long-kai HE Yong-jun XIE Yi-ning |
| author_sort | ZHAO Jing |
| collection | DOAJ |
| description | Automatic screening technology developed in recent years. It applies image processing, and first recognizes nucleus and then measures the DNA contents accurately, so it can provide auxiliary for a doctor′s diagnosis. Image segmentation is the key technique of automatic screening system which directly determines the performance of the systems. However, the imaging environments under the microscope are complex. One the one hand, uneven illumination, background shading and uneven dyed nucleus exist. On the other hand, there are inevitably blood cells, lymphocytes, garbage, impurities and conglobation cells in cell images. These conditions degrade the performance of image segmentation. In order to solve these problems, we put forward a method to segment cervical nuclei in complex background. This method first employs the local threshold method to segment images. In this procedure we propose a parameter adapting method which adjusts its parameters automatically
according to the function of local threshold window size and the binarized outline number. The local threshold method transforms an image into a binary image which is then passed to image corrosion operator to generate a marking image. With the binary image, the watershed algorithm was finally performed to segment the image. The experiment shows that the method can adapt to the complex image environment and separate the cells with lower overlapping nuclei images. |
| format | Article |
| id | doaj-art-e01a17fe302a461b82b4e511caed13d8 |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2019-06-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-e01a17fe302a461b82b4e511caed13d82025-08-20T03:43:43ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832019-06-012403222810.15938/j.jhust.2019.03.004The Method of Segmentation of Cervical Nuclei in Complex BackgroundZHAO Jing0LIANG Long-kai1HE Yong-jun2XIE Yi-ning3Harbin University of Science and Technology, School of Computer Science and Technology, Harbin 150080, ChinaHarbin University of Science and Technology, School of Computer Science and Technology, Harbin 150080, ChinaHarbin University of Science and Technology, School of Computer Science and Technology, Harbin 150080, ChinaHarbin University of Science and Technology, School of Computer Science and Technology, Harbin 150080, ChinaAutomatic screening technology developed in recent years. It applies image processing, and first recognizes nucleus and then measures the DNA contents accurately, so it can provide auxiliary for a doctor′s diagnosis. Image segmentation is the key technique of automatic screening system which directly determines the performance of the systems. However, the imaging environments under the microscope are complex. One the one hand, uneven illumination, background shading and uneven dyed nucleus exist. On the other hand, there are inevitably blood cells, lymphocytes, garbage, impurities and conglobation cells in cell images. These conditions degrade the performance of image segmentation. In order to solve these problems, we put forward a method to segment cervical nuclei in complex background. This method first employs the local threshold method to segment images. In this procedure we propose a parameter adapting method which adjusts its parameters automatically according to the function of local threshold window size and the binarized outline number. The local threshold method transforms an image into a binary image which is then passed to image corrosion operator to generate a marking image. With the binary image, the watershed algorithm was finally performed to segment the image. The experiment shows that the method can adapt to the complex image environment and separate the cells with lower overlapping nuclei images.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1677nucleus segmentationparameter adaptivewatershed algorithmlocal threshold method |
| spellingShingle | ZHAO Jing LIANG Long-kai HE Yong-jun XIE Yi-ning The Method of Segmentation of Cervical Nuclei in Complex Background Journal of Harbin University of Science and Technology nucleus segmentation parameter adaptive watershed algorithm local threshold method |
| title | The Method of Segmentation of Cervical Nuclei in Complex Background |
| title_full | The Method of Segmentation of Cervical Nuclei in Complex Background |
| title_fullStr | The Method of Segmentation of Cervical Nuclei in Complex Background |
| title_full_unstemmed | The Method of Segmentation of Cervical Nuclei in Complex Background |
| title_short | The Method of Segmentation of Cervical Nuclei in Complex Background |
| title_sort | method of segmentation of cervical nuclei in complex background |
| topic | nucleus segmentation parameter adaptive watershed algorithm local threshold method |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1677 |
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