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Decoupling convolution network for characterizing the metastatic lymph nodes of breast cancer patients
Medical Physics ( IF 3.2 ) Pub Date : 2021-04-07 , DOI: 10.1002/mp.14876
Rutong Zeng 1, 2 , Xiang Zhang 3, 4 , Chushan Zheng 3, 4 , Jin-Hong Du 1 , Zixiong Gao 5 , Wei Jun 6 , Jun Shen 3, 4 , Yao Lu 2, 5, 7
Affiliation  

The dual-energy computed tomography (DECT) technique is an emerging imaging tool that can better characterize material features and has the potential to be a noninvasive means of predicting lymph node metastasis. The purpose of this study was to establish a DECT-specified quantitative approach based on a neural network to characterize the sentinel lymph node (SLN).

中文翻译:

用于表征乳腺癌患者转移淋巴结的去耦卷积网络

双能计算机断层扫描 (DECT) 技术是一种新兴的成像工具,可以更好地表征材料特征,并有可能成为预测淋巴结转移的无创手段。本研究的目的是建立一种基于神经网络的 DECT 特定定量方法来表征前哨淋巴结 (SLN)。
更新日期:2021-04-07
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