Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI
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Abstract (arXiv)
We address the problem of multimodal liver segmentation in paired but unregistered T1 and T2-weighted MR images. We compare several strategies described in the literature, with or without multi-task training, with or without pre-registration. We also compare different loss functions (cross-entropy, Dice loss, and three adversarial losses). All methods achieved comparable performances with the exception of a multi-task setting that performs both segmentations at once, which performed poorly.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 28 references that are in the map. First posted on arXiv 18 Jan 2021.
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References · 14
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