Self-Supervised Slice-to-Volume Reconstruction with Gaussian Representations for Fetal MRI

arXiv:2601.22990v2 Announce Type: replace-cross Abstract: Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume reconstruction (SVR) methods are time-consuming and require multiple orthogonal stacks for reconstruction. While learning-based SVR approaches have significantly reduced the time required at the inference stage, they heavily rely on ground truth information for training, which is inaccessible in prac