X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models

• URL: http://arxiv.org/abs/2404.19604v1
• Date: Tue, 30 Apr 2024 14:53:07 GMT
• Title: X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models
• Authors: Emmanuelle Bourigault, Abdullah Hamdi, Amir Jamaludin,
• Abstract summary: X-Diffusion is a cross-sectional diffusion model tailored for Magnetic Resonance Imaging (MRI) data. X-Diffusion is able to generate detailed 3D MRI volume from a single full-body DXA. Remarkably, the resultant MRIs flawlessly retain essential features of the original MRI, including tumour profiles, spine curvature, brain volume, and beyond.
• Score: 6.046082223332061
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• 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 brain tumour MRIs from the BRATS dataset and full-body MRIs from the UK Biobank dataset. Utilizing the paired pre-registered Dual-energy X-ray Absorptiometry (DXA) and MRI modalities in the UK Biobank dataset, X-Diffusion is able to generate detailed 3D MRI volume from a single full-body DXA. Remarkably, the resultant MRIs not only stand out in precision on unseen examples (surpassing state-of-the-art results by large margins) but also flawlessly retain essential features of the original MRI, including tumour profiles, spine curvature, brain volume, and beyond. Furthermore, the trained X-Diffusion model on the MRI datasets attains a generalization capacity out-of-domain (e.g. generating knee MRIs even though it is trained on brains). The code is available on the project website https://emmanuelleb985.github.io/XDiffusion/ .

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