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Found 2 papers, 2 papers with code
SPINEPS -- Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance Segmentation
Training on auto-generated annotations and evaluating on manually corrected test data from the GNC yielded global dice scores of 0. 900 for vertebrae, 0. 960 for intervertebral discs, and 0. 947 for the spinal canal.
Denoising diffusion-based MRI to CT image translation enables automated spinal segmentation
The 3D translation outperformed the 2D approach, resulting in improved Dice scores (0. 80) and anatomically accurate segmentations in a higher resolution than the original MR image.
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