| 游子轩,薛智元,金日初,张珂.深度学习用于分割颞骨CT结构进展[J].中国医学影像技术,2026,42(3):457~461 |
| 深度学习用于分割颞骨CT结构进展 |
| Progresses of deep learning in temporal bone CT structures segmentation |
| 投稿时间：2025-07-14 修订日期：2025-11-09 |
| DOI：10.13929/j.issn.1003-3289.2026.03.028 |
| 中文关键词: 颞骨 体层摄影术,X线计算机 深度学习 图像分割 |
| 英文关键词:temporal bone tomography,X-ray computed deep learning image segmentation |
| 基金项目:国家自然科学基金(62271008)。 |
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| 中文摘要: |
| 精准分割颞骨CT结构是耳科手术规划与诊疗疾病的关键,而传统手动分割存在耗时长、精度低等问题。深度学习技术在医学影像领域展现出显著优势,为分割颞骨CT结构提供了新的解决方案。本文围绕深度学习用于颞骨CT结构分割进展进行综述。 |
| 英文摘要: |
| Accurate segmentation of temporal bone CT structures is a key for ear surgery planning and diagnosis and treatment of diseases, but traditional manual segmentation methods have limits such as long-time consumption and low accuracy. Deep learning (DL) has shown significant advantages in the field of medical imaging, providing a new solution for structures segmentation of temporal bone CT. The progresses of DL in temporal bone CT structures segmentation were reviewed in this article. |
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