Challenges in Evaluating U-Shaped Neural Networks for Medical Image Segmentation

U-shaped neural networks, characterized by their encoder and decoder architectures, have become increasingly popular in the domain of medical image segmentation. Nevertheless, research pertaining to the evaluation of these models lags behind their development. The current evaluation techniques encounter challenges related to complexity and uncertainty in their applicability to clinical practice. Furthermore, the evaluation technology itself is yet to achieve a comprehensive and unified approach.