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. 2021 Sep 22;11:18800. doi: 10.1038/s41598-021-98408-8

Figure 2.

Figure 2

Deep learning architectures for the multimodal pCR prediction model. (A) The feature extractors for contrast-enhanced T1W subtraction MR images and T2W MR images were used in two 3D ResNet-50. The MR images for the input were subjected to isotropic transformation and cropped to a 3D form of 224 × 224 × 64. (B) FC layer was used for clinical information inputs. The outputs of each 3D ResNet-50 and FC layer for clinical information were concatenated. The final FC layer with sigmoid activation function was used in the prediction of pCR.