Self-supervised approach for organs at risk segmentation of abdominal CT images
Accurate segmentation of organs at risk is essential for radiation therapy planning. However, manual segmentation is time-consuming and prone to inter and intra-observer variability. This study proposes a self-supervision based attention UNet model for OAR segmentation of abdominal CT images. The mo...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2023/04/itmconf_I3cs2023_01003.pdf |