TSF U-Net: A Texture-Span and Frequency-Gated U-Net for Brain Tumor MRI Segmentation
Findings indicate that jointly modeling pathological texture variations in the spatial domain and semantically selecting skip features in the frequency domain provides an effective strategy for improving boundary sensitivity, noise resistance, and cross-dataset robustness in brain tumor MRI segmentation.