K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images
In order to improve the global search power of the K-means algorithm and the clustering effect, the K-means method based on the approximate backbone and the shuffled frog leaping algorithm is proposed. Firstly, in this method, the classic iterative formula of the K-means algorithm is replaced by the...
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| Format: | Article |
| Language: | English |
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Editorial Department of Journal of Nantong University (Natural Science Edition)
2020-06-01
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| Series: | Nantong Daxue xuebao. Ziran kexue ban |
| Subjects: | |
| Online Access: | https://ngzk.cbpt.cnki.net/portal/journal/portal/client/paper/NGZK_1f62a914-812d-4717-8477-0ca32726c814 |
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| _version_ | 1850170879824101376 |
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| author | SUN Ying;ZHANG Yi;DING Weiping;JU Hengrong;REN Longjie |
| author_facet | SUN Ying;ZHANG Yi;DING Weiping;JU Hengrong;REN Longjie |
| author_sort | SUN Ying;ZHANG Yi;DING Weiping;JU Hengrong;REN Longjie |
| collection | DOAJ |
| description | In order to improve the global search power of the K-means algorithm and the clustering effect, the K-means method based on the approximate backbone and the shuffled frog leaping algorithm is proposed. Firstly, in this method, the classic iterative formula of the K-means algorithm is replaced by the classic shuffled frog leaping algorithm to obtain multiple sets of better clustering results. Then, the K-means algorithm based on the approximate backbone and the shuffled frog leaping algorithm is used for the obtained clustering results. Instead of searching for cluster centers, the cluster division is directly modified. The experimental results of the UCI dataset reveal that the clustering results obtained by the improved algorithm are better than those of other algorithms. Finally, this study applies the improved clustering algorithm to the medical fundus medical records images, which has a better effect on the vascular cutting. |
| format | Article |
| id | doaj-art-50f2d88878dc4fe6879ab0ba8b5771ca |
| institution | OA Journals |
| issn | 1673-2340 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | Editorial Department of Journal of Nantong University (Natural Science Edition) |
| record_format | Article |
| series | Nantong Daxue xuebao. Ziran kexue ban |
| spelling | doaj-art-50f2d88878dc4fe6879ab0ba8b5771ca2025-08-20T02:20:23ZengEditorial Department of Journal of Nantong University (Natural Science Edition)Nantong Daxue xuebao. Ziran kexue ban1673-23402020-06-011902364210.12194/j.ntu.20191128001K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record ImagesSUN Ying;ZHANG Yi;DING Weiping;JU Hengrong;REN LongjieIn order to improve the global search power of the K-means algorithm and the clustering effect, the K-means method based on the approximate backbone and the shuffled frog leaping algorithm is proposed. Firstly, in this method, the classic iterative formula of the K-means algorithm is replaced by the classic shuffled frog leaping algorithm to obtain multiple sets of better clustering results. Then, the K-means algorithm based on the approximate backbone and the shuffled frog leaping algorithm is used for the obtained clustering results. Instead of searching for cluster centers, the cluster division is directly modified. The experimental results of the UCI dataset reveal that the clustering results obtained by the improved algorithm are better than those of other algorithms. Finally, this study applies the improved clustering algorithm to the medical fundus medical records images, which has a better effect on the vascular cutting.https://ngzk.cbpt.cnki.net/portal/journal/portal/client/paper/NGZK_1f62a914-812d-4717-8477-0ca32726c814k-means algorithmshuffled frog leaping algorithmapproximate backbonefundus medical record images |
| spellingShingle | SUN Ying;ZHANG Yi;DING Weiping;JU Hengrong;REN Longjie K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images Nantong Daxue xuebao. Ziran kexue ban k-means algorithm shuffled frog leaping algorithm approximate backbone fundus medical record images |
| title | K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images |
| title_full | K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images |
| title_fullStr | K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images |
| title_full_unstemmed | K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images |
| title_short | K-means Method Based on the Approximate Backbone and the Shuffled Frog Leaping Algorithm and Its Application in Fundus Medical Record Images |
| title_sort | k means method based on the approximate backbone and the shuffled frog leaping algorithm and its application in fundus medical record images |
| topic | k-means algorithm shuffled frog leaping algorithm approximate backbone fundus medical record images |
| url | https://ngzk.cbpt.cnki.net/portal/journal/portal/client/paper/NGZK_1f62a914-812d-4717-8477-0ca32726c814 |
| work_keys_str_mv | AT sunyingzhangyidingweipingjuhengrongrenlongjie kmeansmethodbasedontheapproximatebackboneandtheshuffledfrogleapingalgorithmanditsapplicationinfundusmedicalrecordimages |