cSVR: Convolutional Slice-to-Volume Reconstruction

Unpredictable fetal motion during MRI scans can result in oblique 2D slices that are difficult to interpret and often leads to prolonged scan times. Slice-to-volume reconstruction (SVR) methods align 2D oblique slices from multiple slice stacks into a coherent 3D volume. We propose a convolutional network that predicts slice poses by performing multiscale, unrolled optimization and further refines them and super-resolves the volume using model-based optimization. Our convolutional feed-forward SVR network achieves accuracy on par with state-of-the-art results while offering significant speedup, paving the way for scanner-side use of SVR. The code is available https://github.com/MedicalVisionGroup/cSVR.