Yihong Zhang1, Ying Hou2, Jie Bao3, Yang Song1, Yu-dong Zhang2, Xu Yan4, and Guang Yang1
1East China Normal University, Shanghai, China, 2the First Affiliated Hospital with Nanjing Medical University, Nanjing, China, 3the First Affiliated Hospital with Soochow University, Soochow, China, 4Siemens Healthcare, Shanghai, China
1East China Normal University, Shanghai, China, 2the First Affiliated Hospital with Nanjing Medical University, Nanjing, China, 3the First Affiliated Hospital with Soochow University, Soochow, China, 4Siemens Healthcare, Shanghai, China
We incorporated prior-knowledge into a CNN
model to diagnosis ECE from mpMRI. Our model performed better than the
classical CNN model and clinical reports on both the internal and external test
cohorts.
Figure 1 The workflow of the research. We trained the PAGNet
on training cohort from one-site, and evaluated its performance with cohorts
from both institutions. The performance of the proposed model was compared with
those of a ResNeXt model and two radiologists.
Figure
4 ROC
curves (top) and Grad-CAM of PAGNet (bottom). PAGNet performed better than ResNeXt
model and clinical reports in the internal test cohort (a), and achieved
results comparable to the radiologists on the external cohort (b). The
Grad-CAMs of the model on one positive case (c) and one negative case (d) were
also shown, in which the red regions indicate where the model paid attention.
