SPLIT partitions projection data to enforce cross-consistency and measurement fidelity, proving that its self-supervised objective matches supervised training in expectation under mild conditions, with strong results on sparse-view multispectral CT.
Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography.Inverse Problems, 34(6):064001, 2018
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SPLIT: Self-supervised Partitioning for Learned Inversion in Nonlinear Tomography
SPLIT partitions projection data to enforce cross-consistency and measurement fidelity, proving that its self-supervised objective matches supervised training in expectation under mild conditions, with strong results on sparse-view multispectral CT.