An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR
Automated cell segmentation in cervical cytology images is an essential task because it can present a deep understanding of the characteristics of cervical cells. The main challenge is that cells overlap at a high rate, making the cell boundaries extremely blurred. While the transformer-based models...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10766582/ |
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| author | Baocan Zhang Xiaolu Jiang Wei Zhao |
| author_facet | Baocan Zhang Xiaolu Jiang Wei Zhao |
| author_sort | Baocan Zhang |
| collection | DOAJ |
| description | Automated cell segmentation in cervical cytology images is an essential task because it can present a deep understanding of the characteristics of cervical cells. The main challenge is that cells overlap at a high rate, making the cell boundaries extremely blurred. While the transformer-based models have been proven to be effective in vision tasks, this paper proposes an enhanced mask transformer based on DETR to segment overlapping cervical cells. Dynamic anchor box initialization and noised ground truth box embedding are introduced, to improve segmentation performance and accelerate model convergence. The proposed model achieves a 0.974 DSC, 0.971 TPRp, 0.0005 FPRp and 0.0012 FNRo on the ISBI2014 dataset. Specially, the proposed method outperforms state-of-the-art result by about 3.4% on DSC, 2% on TPRp and 1.88% on FNRo, respectively. The metrics of our model on the ISBI2015 dataset are a little better than the averaged metrics of other impressive methods. These findings present strong support for the transformer-based neural networks for effective segmentation of cells in cervical cytology images. |
| format | Article |
| id | doaj-art-7c8e5a3c8e344cd8bf642bb0e1d9e667 |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-7c8e5a3c8e344cd8bf642bb0e1d9e6672025-08-20T02:19:54ZengIEEEIEEE Access2169-35362024-01-011217658617659710.1109/ACCESS.2024.350561610766582An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETRBaocan Zhang0https://orcid.org/0000-0001-8421-6404Xiaolu Jiang1https://orcid.org/0000-0002-9290-284XWei Zhao2https://orcid.org/0000-0002-6814-1526Chengyi College, Jimei University, Xiamen, Fujian, ChinaChengyi College, Jimei University, Xiamen, Fujian, ChinaChengyi College, Jimei University, Xiamen, Fujian, ChinaAutomated cell segmentation in cervical cytology images is an essential task because it can present a deep understanding of the characteristics of cervical cells. The main challenge is that cells overlap at a high rate, making the cell boundaries extremely blurred. While the transformer-based models have been proven to be effective in vision tasks, this paper proposes an enhanced mask transformer based on DETR to segment overlapping cervical cells. Dynamic anchor box initialization and noised ground truth box embedding are introduced, to improve segmentation performance and accelerate model convergence. The proposed model achieves a 0.974 DSC, 0.971 TPRp, 0.0005 FPRp and 0.0012 FNRo on the ISBI2014 dataset. Specially, the proposed method outperforms state-of-the-art result by about 3.4% on DSC, 2% on TPRp and 1.88% on FNRo, respectively. The metrics of our model on the ISBI2015 dataset are a little better than the averaged metrics of other impressive methods. These findings present strong support for the transformer-based neural networks for effective segmentation of cells in cervical cytology images.https://ieeexplore.ieee.org/document/10766582/Cervical cell segmentationDETRISBI datasetstransformer |
| spellingShingle | Baocan Zhang Xiaolu Jiang Wei Zhao An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR IEEE Access Cervical cell segmentation DETR ISBI datasets transformer |
| title | An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR |
| title_full | An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR |
| title_fullStr | An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR |
| title_full_unstemmed | An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR |
| title_short | An Enhanced Mask Transformer for Overlapping Cervical Cell Segmentation Based on DETR |
| title_sort | enhanced mask transformer for overlapping cervical cell segmentation based on detr |
| topic | Cervical cell segmentation DETR ISBI datasets transformer |
| url | https://ieeexplore.ieee.org/document/10766582/ |
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