May 1, 2024, 4:46 a.m. | Emmanuelle Bourigault, Abdullah Hamdi, Amir Jamaludin

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.19604v1 Announce Type: cross
Abstract: In this work, we present X-Diffusion, a cross-sectional diffusion model tailored for Magnetic Resonance Imaging (MRI) data. X-Diffusion is capable of generating the entire MRI volume from just a single MRI slice or optionally from few multiple slices, setting new benchmarks in the precision of synthesized MRIs from extremely sparse observations. The uniqueness lies in the novel view-conditional training and inference of X-Diffusion on MRI volumes, allowing for generalized MRI learning. Our evaluations span both …

arxiv cs.cv diffusion diffusion models eess.iv image mri type

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