Fig 1.
Flowchart of the pipeline. A, Preprocessing is performed with 4 different models. The dataset is split into test, training, and validation sets. B, Inference is performed with the convolutional neural network DeepMedic with a 2-pathway architecture. The number of feature maps and their size is depicted as number × size. The + depicts the addition of the 2 preceding layers, which adds an additional nonlinearity and reduces the number of weights.18 The diagram is based on the depiction in the DeepMedic documentation. (Modified from Kamnitsas K, Ledig C, Newcombe VFJ, et al. Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation. Medical Image Analysis 2017;36:61–78 under CC-BY4 license).32 C, Thresholding is applied to the resulting segmentation and evaluated with different metrics. LN indicates layers in the normal resolution pathway, LL indicates layers in the low resolution pathway.