Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm
With the development of artificial intelligence technology, the automatic reading system plays an increasingly important role in assisting the diagnosis of pathologists, improving the accuracy of pathology diagnosis and reducing labor intensity. Accurate segmentation of the nucleus is the primary fa...
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| Format: | Article |
| Language: | zho |
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Harbin University of Science and Technology Publications
2021-12-01
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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=2029 |
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| author | HE Yong jun ZHANG Xue yuan SHAO Hui li DING Bo |
| author_facet | HE Yong jun ZHANG Xue yuan SHAO Hui li DING Bo |
| author_sort | HE Yong jun |
| collection | DOAJ |
| description | With the development of artificial intelligence technology, the automatic reading system plays an increasingly important role in assisting the diagnosis of pathologists, improving the accuracy of pathology diagnosis and reducing labor intensity. Accurate segmentation of the nucleus is the primary factor affecting the performance of the automated reading system. Because the boundary between the nucleus, the cytoplasm and the background is unclear, and the color difference between the cells is large, the nuclear segmentation is challenged. In order to solve this problem, a method of cervical nucleus segmentation based on optimal maximum stability regions(Maximally Stable Extremal Regions, MSER) algorithm is proposed. This method first converts the image to the HSV (Hue, Saturation, Value) color space. Then, after weighted combination of S and V channels, the optimized MSER algorithm is used to obtain a coarse segmentation region with uniform gray values. The parameter segmentation method is used to perform fine segmentation. Finally, the feature extraction technique is used to extract various features from the nuclear image, and the artificial neural network classifier is trained to judge whether the result obtained after segmentation is the nucleus. Experiments show that the method can accurately segment the cervical nucleus |
| format | Article |
| id | doaj-art-bb8c00778a8646aeaebd90c1b41ba60f |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2021-12-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-bb8c00778a8646aeaebd90c1b41ba60f2025-08-20T03:34:13ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832021-12-012606101710.15938/j.jhust.2021.06.002Cervical Cell Nuclear Segmentation Method Based on Optimized MSER AlgorithmHE Yong jun0ZHANG Xue yuan1SHAO Hui li2DING Bo3School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, ChinaWith the development of artificial intelligence technology, the automatic reading system plays an increasingly important role in assisting the diagnosis of pathologists, improving the accuracy of pathology diagnosis and reducing labor intensity. Accurate segmentation of the nucleus is the primary factor affecting the performance of the automated reading system. Because the boundary between the nucleus, the cytoplasm and the background is unclear, and the color difference between the cells is large, the nuclear segmentation is challenged. In order to solve this problem, a method of cervical nucleus segmentation based on optimal maximum stability regions(Maximally Stable Extremal Regions, MSER) algorithm is proposed. This method first converts the image to the HSV (Hue, Saturation, Value) color space. Then, after weighted combination of S and V channels, the optimized MSER algorithm is used to obtain a coarse segmentation region with uniform gray values. The parameter segmentation method is used to perform fine segmentation. Finally, the feature extraction technique is used to extract various features from the nuclear image, and the artificial neural network classifier is trained to judge whether the result obtained after segmentation is the nucleus. Experiments show that the method can accurately segment the cervical nucleushttps://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2029nuclear segmentationstable regionconvex hull detectioncolor space |
| spellingShingle | HE Yong jun ZHANG Xue yuan SHAO Hui li DING Bo Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm Journal of Harbin University of Science and Technology nuclear segmentation stable region convex hull detection color space |
| title | Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm |
| title_full | Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm |
| title_fullStr | Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm |
| title_full_unstemmed | Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm |
| title_short | Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm |
| title_sort | cervical cell nuclear segmentation method based on optimized mser algorithm |
| topic | nuclear segmentation stable region convex hull detection color space |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2029 |
| work_keys_str_mv | AT heyongjun cervicalcellnuclearsegmentationmethodbasedonoptimizedmseralgorithm AT zhangxueyuan cervicalcellnuclearsegmentationmethodbasedonoptimizedmseralgorithm AT shaohuili cervicalcellnuclearsegmentationmethodbasedonoptimizedmseralgorithm AT dingbo cervicalcellnuclearsegmentationmethodbasedonoptimizedmseralgorithm |