HiP-CT Enables Multiscale Segmentation With Deep Learning

Zhou et al., published February 2, 2026, present a deep learning pipeline that leverages Hierarchical Phase-Contrast Tomography (HiP-CT) multiscale scans to segment small functional units across whole organs. Trained on high-resolution VOIs and using pseudo-labels to extend predictions to ca. 25 /voxel whole-kidney scans, nnUNet achieved a test Dice of 0.906 and detected 1,019,890 and 231,179 glomeruli in two donors. The pipeline enables comprehensive 3D morphological and spatial analyses at organ scale.