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A Unet-based Research on the Multi-Output Convolution Neural Network's Ability of Decreasing Mis-identification: Automatic Segmentation of Organs at Risk in Thorax

机译：基于UNET的多输出卷积神经网络减少误识别能力的研究：胸部风险的机动器官的自动分割

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Jie Zhang; Yiwei Yang; Kainan Shao; Xue Bai; Min Fang; Guoping Shan; Ming Chen;
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1. Auto Segmentation of Organs at Risk in Thorax Computed Tomography Using Deep Convolutional Neural Networks [J] . Haytmyradov M., Surucu M., Cassetta F., Medical Physics . 2019,第6期

机译：使用深卷积神经网络的胸部计算机断层扫描的风险的机构的自动分割
2. Deep convolutional neural networks for automatic segmentation of thoracic organs‐at‐risk in radiation oncology – use of non‐domain transfer learning [J] . Charles C. Vu, Zaid A. Siddiqui, Leonid Zamdborg, Journal of applied clinical medical physics / . 2020,第6期

机译：深度卷积神经网络，用于胸内肿瘤内肿瘤的自动分割 - 非域转移学习的使用
3. Automatic segmentation of the clinical target volume and organs at risk in the planning CT CT for rectal cancer using deep dilated convolutional neural networks [J] . Men Kuo, Dai Jianrong, Li Yexiong Medical Physics . 2017,第12期

机译：使用深扩张的卷积神经网络的直肠癌患者CT CT的临床目标体积和器官的自动分割
4. Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks [C] . Liesbeth Vandewinckele, David Robben, Wouter Crijns, International conference on medical imaging computing and computer-assisted intervention;International workshop on deep learning in medical image analysis;International workshop on multimodal learning for clinical decision support . 2018

机译：结合可变形配准和卷积神经网络的纵向CT扫描中头颈部器官风险的分割
5. Automated Segmentation and Uncertainty Quantification for Image-Based Cardiovascular Modeling with Convolutional Neural Networks [D] . Maher, Gabriel. 2020

机译：卷积神经网络的图像基础心血管建模的自动分割和不确定量化
6. Deep convolutional neural networks for automatic segmentation of thoracic organs‐at‐risk in radiation oncology – use of non‐domain transfer learning [O] . Charles C. Vu, Zaid A. Siddiqui, Leonid Zamdborg, 2020

机译：深度卷积神经网络可自动分割放射肿瘤中处于危险中的胸腔器官-使用非域转移学习
7. Automatic Segmentation of Clinical Target Volume and Organs-At-Risk for Breast Conservative Radiotherapy Using a Convolutional Neural Network [O] . Zhikai Liu, Fangjie Liu, Wanqi Chen, 2021

机译：使用卷积神经网络自动分割临床目标体积和器官的乳房保守放疗的风险

A Unet-based Research on the Multi-Output Convolution Neural Network's Ability of Decreasing Mis-identification: Automatic Segmentation of Organs at Risk in Thorax

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