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深度学习促进了总骨髓和总淋巴细胞辐射的目标体积的划分,用于加速放射治疗:一项多机构研究

Xudong Xue1, Jun Shi2, Hui Zeng3

  • 1Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, China; Department of Radiation Oncology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
|June 9, 2024
PubMed
概括

一个新的深度学习模型,DEA-Net,通过自动化瘤点细分来显著加快放射治疗的规划,用于总髓辐射 (TMI) 和总髓和淋巴细胞辐射 (TMLI). 这种混合网络实现了高精度,减少了98%的规划时间.

关键词:
自动细分可以实现.深度学习是一种深度学习.这就是TMI TMI.TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI TMLI

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