SwinD-Net: a lightweight segmentation network for laparoscopic liver segmentation
The real-time requirement for image segmentation in laparoscopic surgical assistance systems is extremely high. Although traditional deep learning models can ensure high segmentation accuracy, they suffer from a large computational burden. In the practical setting of most hospitals, where powerful c...
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| Main Authors: | Shuiming Ouyang, Baochun He, Huoling Luo, Fucang Jia |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Computer Assisted Surgery |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/24699322.2024.2329675 |
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