Fig. 1: We study the ability of diffusion models to generate digital siblings for virtual interventions and augment in silico trials.
From: Probing the limits and capabilities of diffusion models for the anatomic editing of digital twins
Top row: we unconditionally generate latent codes \((\bar{{\bf{z}}})\) which are decoded (D) into cardiac label maps (\(\bar{{\bf{x}}}\)). Middle row: We encode (E) patient-specific digital twins (x) into a latent space (z) and apply a partial perturb-denoise process to achieve scale-specific variations (\({\bar{{\bf{x}}}}_{\psi }\)). Bottom row: We locally edit pre-specified tissues to achieve region-specific variations (\({\bar{{\bf{x}}}}_{{\bf{m}}}\)).
