Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models.

Prior knowledge about the shape of the target organ can improve the performance of CNN-based segmentation methods, especially where image features are not sufficient for a precise segmentation. Statistical shape models can also be employed to synthesize additional training data that can ease the training of large CNNs.