C2W-Tune transfers weights from a pre-trained LA cavity model to achieve higher accuracy in thin atrial wall segmentation, raising Dice from 0.623 to 0.814 on the 2018 LA challenge dataset.
et al.: Convolutional neural networks for medical image analysis: full training or fine tuning? IEEE Trans
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C2W-Tune: Cavity-to -Wall Transfer Learning for Thin Atrial Wall Segmentation in 3D LGE-MRI
C2W-Tune transfers weights from a pre-trained LA cavity model to achieve higher accuracy in thin atrial wall segmentation, raising Dice from 0.623 to 0.814 on the 2018 LA challenge dataset.