| 王子怡,孙佳伟,张赛,张恒,倪昕晔.锥形束CT图像分割方法研究进展[J].中华放射医学与防护杂志,2023,43(1):73-77 |
| 锥形束CT图像分割方法研究进展 |
| Research on con-beam CT images segmentation method |
| 投稿时间：2022-09-27 |
| DOI：10.3760/cma.j.cn112271-20220927-00392 |
| 中文关键词: 锥形束CT 图像分割 深度学习 |
| 英文关键词:Cone beam CT Image segmentation Deep learning |
| 基金项目:江苏省重点研发计划社会发展项目(BE2022720);江苏省卫健委面上项目(M2020006) |
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| 中文摘要: |
| 图像引导放射治疗(IGRT)是一种可视化的影像引导放疗技术,具有提高肿瘤靶区剂量,降低正常器官受照剂量等诸多优点。锥形束CT(CBCT)是IGRT中最常用的医学图像之一,对CBCT进行快速、准确的靶区及危及器官的分割对放疗具有重大意义。目前的研究方法主要有基于配准的分割方法和基于深度学习的分割方法。本研究针对CBCT图像分割方法、存在问题及发展方向进行综述。 |
| 英文摘要: |
| Image-guided radiation therapy (IGRT) is a visual image-guided radiotherapy technique that has many advantages such as increasing the dose of tumor target area and reducing the dose of normal organ exposure. Cone beam CT (CBCT) is one of the most commonly used medical images in IGRT, and the rapid and accurate targeting of CBCT and the segmentation of dangerous organs are of great significance for radiotherapy. The current research method mainly includes partitioning method based on registration and segmentation method based on deep learning. This study reviews the CBCT image segmentation method, existing problems and development directions. |
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