Vertebra CT Image Segmentation Method Based on Improved U-Net Model
In view of the problem that the classical u-net model does not make full use of the image information during the CT segmentation of vertebrae，which leads to unclear image edge segmentation，an improved algorithm of CT image segmentation of vertebrae based on the u-net model is proposed. Firstly，it wa...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2021-06-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1975 |
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| Summary: | In view of the problem that the classical u-net model does not make full use of the image information during the CT segmentation of vertebrae，which leads to unclear image edge segmentation，an improved algorithm of CT image segmentation of vertebrae based on the u-net model is proposed. Firstly，it was improved and optimized on the basis of the classic u-net model. Then，the improved u-net model was used to segment the vertebral region and obtain the rough segmentation result. Finally，the rough segmentation result was strengthened by the edge constraint algorithm ( Graph-Cut ) so as to achieve the edge refinement segmentation. In this paper， the segmentation precision of the methord can be reached 95. 5% . The Dice coefficient is 96. 2% . The Jaccard coefficient is 92. 6% . The HdD index is 4. 88. Compared with the classic u-net model，the Dice coefficient increased by 2. 2%，the Jaccard coefficient increased by 3. 7%，and the HdD index decreased by 13. 9%. |
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| ISSN: | 1007-2683 |