Evaluating U-Shaped Neural Networks for Multi-Organ Segmentation: A Critical Assessment of Current Methods

The application of U-shaped neural networks, characterized by encoder and decoder structures, has gained significant traction within the field of medical image segmentation. Despite the advancements in model development, the existing methods for evaluating these models face significant challenges in terms of their complexity and their ability to provide actionable insights for clinical practice. Notably, the current evaluation techniques are insufficiently comprehensive, particularly in the context of specific clinical application scenarios such as multi-organ segmentation tasks, where evaluation methodologies remain underdeveloped.