MSDEnet: Multi-scale detail enhanced network based on human visual system for medical image segmentation.

In medical image segmentation, accuracy is commonly high for tasks involving clear boundary partitioning features, as seen in the segmentation of X-ray images. However, for objects with less obvious boundary partitioning features, such as skin regions with similar color textures or CT images of adjacent organs with similar Hounsfield value ranges, segmentation accuracy significantly decreases. Inspired by the human visual system, we proposed the multi-scale detail enhanced network.