An improved method of microscopic image segmentation
In order to improve the effectiveness and accuracy of image processing in modern medical inspection, a segmentation image optimization algorithm of improved two-dimensional maximum entropy threshold based on genetic algorithm combined with mathematical morphology is proposed, in view of the microsco...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2018-01-01
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| Series: | MATEC Web of Conferences |
| Online Access: | https://doi.org/10.1051/matecconf/201817601041 |
| _version_ | 1819276042240524288 |
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| author | Feng Shou Zhang Fang Dong Jian Ting Liu Xin Meng |
| author_facet | Feng Shou Zhang Fang Dong Jian Ting Liu Xin Meng |
| author_sort | Feng Shou Zhang |
| collection | DOAJ |
| description | In order to improve the effectiveness and accuracy of image processing in modern medical inspection, a segmentation image optimization algorithm of improved two-dimensional maximum entropy threshold based on genetic algorithm combined with mathematical morphology is proposed, in view of the microscopic cell images characteristic and the shortcomings of the traditional segmentation algorithm. Through theoretical analysis and contrast test, the segmentation method proposed is superior to the traditional threshold segmentation method in microscopic cell images, and the average segmentation time of the improved algorithm is 73% and 44% higher than the traditional two-dimensional maximum entropy threshold and the improved two-dimensional maximum entropy threshold. |
| first_indexed | 2024-12-23T23:33:55Z |
| format | Article |
| id | doaj.art-057cae64b4ed4ce887998cbacb0cf2e4 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-23T23:33:55Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-057cae64b4ed4ce887998cbacb0cf2e42022-12-21T17:25:56ZengEDP SciencesMATEC Web of Conferences2261-236X2018-01-011760104110.1051/matecconf/201817601041matecconf_ifid2018_01041An improved method of microscopic image segmentationFeng Shou ZhangFang DongJian Ting LiuXin MengIn order to improve the effectiveness and accuracy of image processing in modern medical inspection, a segmentation image optimization algorithm of improved two-dimensional maximum entropy threshold based on genetic algorithm combined with mathematical morphology is proposed, in view of the microscopic cell images characteristic and the shortcomings of the traditional segmentation algorithm. Through theoretical analysis and contrast test, the segmentation method proposed is superior to the traditional threshold segmentation method in microscopic cell images, and the average segmentation time of the improved algorithm is 73% and 44% higher than the traditional two-dimensional maximum entropy threshold and the improved two-dimensional maximum entropy threshold.https://doi.org/10.1051/matecconf/201817601041 |
| spellingShingle | Feng Shou Zhang Fang Dong Jian Ting Liu Xin Meng An improved method of microscopic image segmentation MATEC Web of Conferences |
| title | An improved method of microscopic image segmentation |
| title_full | An improved method of microscopic image segmentation |
| title_fullStr | An improved method of microscopic image segmentation |
| title_full_unstemmed | An improved method of microscopic image segmentation |
| title_short | An improved method of microscopic image segmentation |
| title_sort | improved method of microscopic image segmentation |
| url | https://doi.org/10.1051/matecconf/201817601041 |
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