Encoding feature supervised UNet++: Redesigning Supervision for liver and tumor segmentation. (arXiv:2211.08146v1 [eess.IV])

Liver tumor segmentation in CT images is a critical step in the diagnosis,
surgical planning and postoperative evaluation of liver disease. An automatic
liver and tumor segmentation method can greatly relieve physicians of the heavy
workload of examining CT images and better improve the accuracy of diagnosis.
In the last few decades, many modifications based on U-Net model have been
proposed in the literature. However, there are relatively few improvements for
the advanced UNet++ model. In our paper, we propose …

arxiv encoding feature segmentation unet