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We address the problem of multimodal liver segmentation in paired butunregistered T1 and T2-weighted MR images. We compare several strategiesdescribed in the literature, with or without multi-task training, with orwithout pre-registration. We also compare different loss functions(cross-entropy, Dice loss, and three adversarial losses). All methods achievedcomparable performances with the exception of a multi-task setting thatperforms both segmentations at once, which performed poorly.

Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI