| 深度学习CT图像迭代重建及其用于儿童CT进展 |
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| 引用本文： | 李蕊,崔磊. 深度学习CT图像迭代重建及其用于儿童CT进展[J]. 中国医学影像技术, 2023, 39(2): 303-306 |
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| 作者姓名： | 李蕊 崔磊 |
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| 作者单位： | 南通大学医学院, 江苏 南通 226001;南通大学第二附属医院影像科, 江苏 南通 226001 |
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| 摘 要： | 人工智能在分割、重建医学及图像处理等方面均发挥重要作用。儿童CT检查应遵循尽可能低辐射剂量原则，即在低辐射剂量下最大限度保持或获得更高图像质量。本文对基于人工智能的深度学习CT图像迭代重建技术及其用于儿童CT进展进行综述。
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| 关 键 词： | 体层摄影术,X线计算机 深度学习 儿童 图像质量 |
| 收稿时间： | 2022-06-25 |
| 修稿时间： | 2022-09-03 |
Progresses of CT image iterative reconstruction technique based on deep learning and applications in pediatric CT |
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| LI Rui,CUI Lei. Progresses of CT image iterative reconstruction technique based on deep learning and applications in pediatric CT[J]. Chinese Journal of Medical Imaging Technology, 2023, 39(2): 303-306 |
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| Authors: | LI Rui CUI Lei |
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| Affiliation: | Medical School, Nantong University, Nantong 226001, China;Department of Radiology, the Second Affiliated Hospital of Nantong University, Nantong 226001, China |
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| Abstract: | Artificial intelligence plays an important role in segmentation, reconstruction and processing of medical imaging. Children''s CT examination should follow the principle of low radiation dose as far as possible, that is to maintain or obtain higher image quality at low radiation dose. The progresses of CT image iterative reconstruction technique based on deep learning and applications in pediatric CT were reviewed in this article. |
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| Keywords: | tomography, X-ray computed deep learning child image quality |
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