基于自监督网络的肝脏磁共振R2*参数图像重建
陆琪琪,连梓锋,李嘉龙,斯文彬,麦兆华,冯衍秋*(
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Magnetic Resonance R2* Parameter Mapping of Liver Based on Self-supervised Deep Neural Network
LU Qiqi,LIAN Zifeng,LI Jialong,SI Wenbin,MAI Zhaohua,FENG Yanqiu*()
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图6. 临床肝脏测试数据应用不同方法估计得到的肝实质内（排除了血管结构）的平均$R^{*}_{2}$值与PCANR算法的结果之间的一致性分析. 图中实线代表平均偏差，虚线代
Fig. 6. Bland-Altman analysis for the agreement of the mean $R^{*}_{2}$ values in liver parenchyma (excluding vasculatures) with the reference, and the $R^{*}_{2}$ maps reconstructed from other methods on the clinical testing datasets. The PCANR algorithm was used as the reference method. The solid lines represent mean differences and the dashed lines indicate 95% confidence intervals
