分类与摘要
聚焦医学影像分割、诊断或数据选择，体现 AI 方法在临床相关任务中的应用。
引用
Hongyu Kan*, Jun Shi, Minfan Zhao，Wenting Han*, Hong An, Zhaohui Wang，ITUnet: Integration Of Transformers And Unet For Organs-At-Risk Segmentation，in the proceeding of 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)，Scotland UK, July 11-15, 2022（CCF B）
@article{acsa2022_50,
title = {ITUnet: Integration Of Transformers And Unet For Organs-At-Risk Segmentation},
year = {2022},
doi = {10.1109/embc48229.2022.9871945}
}| title | ITUnet: Integration Of Transformers And Unet For Organs-At-Risk Segmentation |
|---|---|
| title_zh | 待补充 |
| abstract | 待补充 |
| abstract_zh | 待补充 |
| keywords | Medical, 学位认定 B, CCF B |
| year | 2022 |
| published_date | 待补充 |
| online_date | 待补充 |
| paper_type | Conference |
| publication_status | Published |
| volume | 待补充 |
| issue | 待补充 |
| pages | 待补充 |
| article_number | 待补充 |
| publisher | IEEE |
| doi | 10.1109/embc48229.2022.9871945 |
| research_area | 医学影像与智能诊断 |
| tags | Medical, 学位认定 B, CCF B |
| category | 医学影像与智能诊断 |
| summary | 聚焦医学影像分割、诊断或数据选择，体现 AI 方法在临床相关任务中的应用。 |
| authors | Hongyu Kan, Jun Shi, Minfan Zhao, Wenting Han, Hong An, Zhaohui Wang |
| corresponding_authors | 待补充 |
| affiliations | 待补充 |
| funding | 待补充 |