A LinkNet-34 model with transfer learning, augmentation, and a BCE-plus-Dice loss reaches DICE 78.8% for liver tumors on 3DIRCADb and 67.4% tumor DICE on KiTS-2019.
AHCNet: An Applica- tion of Attention Mechanism and Hybrid Connection for Liver Tumor Segmentation in CT Volumes
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Automatic segmentation of kidney and liver tumors in CT images
A LinkNet-34 model with transfer learning, augmentation, and a BCE-plus-Dice loss reaches DICE 78.8% for liver tumors on 3DIRCADb and 67.4% tumor DICE on KiTS-2019.