A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras

arXiv:2210.01607v2 Announce Type: replace-cross
Abstract: Generating virtual populations of anatomy that capture sufficient variability while remaining plausible is essential for conducting in-silico trials of medical devices. However, not all anatomical shapes of interest are always available for each individual in a population. Hence, missing/partially-overlapping anatomical information is often available across individuals in a population. We introduce a generative shape model for complex anatomical structures, learnable from datasets of unpaired datasets. The proposed generative model can synthesise complete whole complex shape …

abstract arxiv cs.cv cs.lg devices eess.iv framework generative information medical medical devices population type virtual