CaLID claims state-of-the-art 3D cardiac volume reconstruction from sparse 2D MRI slices via latent-space diffusion interpolation with a 24x speedup and no auxiliary inputs, but verification is impossible because the supplied manuscript body is a different paper.
When it’s all piling up: investigating error propagation in an NLP pipeline
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Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction
CaLID claims state-of-the-art 3D cardiac volume reconstruction from sparse 2D MRI slices via latent-space diffusion interpolation with a 24x speedup and no auxiliary inputs, but verification is impossible because the supplied manuscript body is a different paper.