SSAD: Prior-driven self-supervised staircase artifact denoising via diffeomorphic flow for volumetric medical image surface reconstruction.
SSAD is proposed, a prior-driven self-supervised framework which redefines reconstruction as learning a diffeomorphic flow from boundary voxels to the coherent optimal surface, and demonstrates a super-resolution capability, with the accuracy of its reconstructed surfaces comparable to that achieved by voxel data at 2-...