Web: http://arxiv.org/abs/2209.06861

Sept. 16, 2022, 1:14 a.m. | David Lüdke, Tamaz Amiranashvili, Felix Ambellan, Ivan Ezhov, Bjoern Menze, Stefan Zachow

cs.CV updates on arXiv.org arxiv.org

Statistical shape modeling aims at capturing shape variations of an
anatomical structure that occur within a given population. Shape models are
employed in many tasks, such as shape reconstruction and image segmentation,
but also shape generation and classification. Existing shape priors either
require dense correspondence between training examples or lack robustness and
topological guarantees. We present FlowSSM, a novel shape modeling approach
that learns shape variability without requiring dense correspondence between
training instances. It relies on a hierarchy of continuous …

arxiv flow free modeling statistical

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