| 岳珂娟,伍炯星,谢东.领域自适应方法用于医学影像研究进展[J].中国医学影像技术,2024,40(6):936~939 |
| 领域自适应方法用于医学影像研究进展 |
| Research progresses of domain adaptive methods for medical imaging |
| 投稿时间：2023-10-07 修订日期：2024-02-21 |
| DOI：10.13929/j.issn.1003-3289.2024.06.029 |
| 中文关键词: 机器学习 诊断显像 领域自适应 域偏移 |
| 英文关键词:machine learning diagnostic imaging domain adaptation domain shift |
| 基金项目:湖南省自然科学基金(2021JJ30173)、国家留学基金资助(留金项[2022]20号,202208430070)。 |
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| 中文摘要: |
| 人工智能有助于提高医学影像学诊断准确率、提高工作效率,但训练模型的过程中需要对大量图像数据进行标注,且需面临域偏移等问题;利用领域自适应方法可基于少量标注数据训练高效模型。本文就领域自适应方法用于医学影像研究进展进行综述。 |
| 英文摘要: |
| Artificial intelligence (AI) can help improve the accuracy and efficiency of medical imaging diagnosis, but training models needs a large amount of image data to be annotated, also faces problems such as domain shift. Using domain adaptive methods can train efficient models based on a small amount of annotated data. The research progresses of domain adaptive methods for medical imaging were reviewed in this article. |
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