基于对抗学习与交叉注意力的多任务阿尔茨海默病分类

顾佳佳, 王远军

Multi-task Alzheimer's Disease Classification Based on Adversarial Learning and Cross-attention

GU Jiajia, WANG Yuanjun

图4 不同模块的ROC曲线（AD、MCI和NC）. (a) MRI作为CNN模型的输入；(b) PET作为CNN模型的输入；(c) MRI和PET作为CNN模型的输入；(d) MRI、PET和年龄作为ALMT模型的输入；(e) MRI、PET和年龄作为ALMCFM模型的输入；(f) MRI、PET和年龄作为MCFMMT模型的输入；(g) MRI、PET和年龄作为MACNet模型的输入

Fig. 4 ROC curves of different modules (AD, MCI, and NC). (a) using MRI as the input to the CNN model; (b) using PET as the input to the CNN model; (c) using both MRI and PET as the inputs to the CNN model; (d) using both MRI, PET and age as the inputs to the ALMT model; (e) using both MRI, PET and age as the inputs to the ALMCFM model; (f) using both MRI, PET and age as the inputs to the MCFMMT model; (g) using both MRI, PET and age as the inputs to the MACNet model