Sli2Vol+ learns slice-to-slice correspondences with guidance from pseudo-labels, improving single-slice-annotated 3D segmentation over the Sli2Vol baseline by about 5.6 Dice points on CT and 3.5 on MRI.
V ol2Flow: Segment 3D volumes using a sequence of registration flows
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Sli2Vol+: Segmenting 3D Medical Images Based on an Object Estimation Guided Correspondence Flow Network
Sli2Vol+ learns slice-to-slice correspondences with guidance from pseudo-labels, improving single-slice-annotated 3D segmentation over the Sli2Vol baseline by about 5.6 Dice points on CT and 3.5 on MRI.