Adaptively weighted Tversky and cross-entropy losses improve UNet-3D pancreas segmentation Dice from 76.11% to 85.59% on the NIH Pancreas-CT dataset.
An optimized two stage U-Net approach for segmentation of pancreas and pancreatic tumor, MethodsX, vol
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UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation
Adaptively weighted Tversky and cross-entropy losses improve UNet-3D pancreas segmentation Dice from 76.11% to 85.59% on the NIH Pancreas-CT dataset.