Copyright
©The Author(s) 2020.
World J Gastroenterol. Jul 7, 2020; 26(25): 3660-3672
Published online Jul 7, 2020. doi: 10.3748/wjg.v26.i25.3660
Published online Jul 7, 2020. doi: 10.3748/wjg.v26.i25.3660
Figure 5 Predicted probability heatmaps.
The top color bar represents the classification probability of the model from 0 to 1, which corresponds to dark blue to bright yellow. A: Shows the results from normal four-phase input; B: Shows the results from different “phase cheating” sets as indicated in the policy of input data; C: Shows the representative examples. AP: Arterial phase; DP: Delayed phase; PP: Precontrast phase; PVP: Portal venous phase.
- Citation: Cao SE, Zhang LQ, Kuang SC, Shi WQ, Hu B, Xie SD, Chen YN, Liu H, Chen SM, Jiang T, Ye M, Zhang HX, Wang J. Multiphase convolutional dense network for the classification of focal liver lesions on dynamic contrast-enhanced computed tomography. World J Gastroenterol 2020; 26(25): 3660-3672
- URL: https://www.wjgnet.com/1007-9327/full/v26/i25/3660.htm
- DOI: https://dx.doi.org/10.3748/wjg.v26.i25.3660