Abstract
Shape analysis aims at analysing the geometrical properties of a given object (e.g. organ or bone). Given a set of shapes, statistics can be estimated and modelled from this training population. Such models are useful to classify healthy and pathological subjects or to generate shape priors for image segmentation. Model construction involves establishment of corresponding points and shape parameterization is a common approach to solve this task, but inevitably introduces dis-tortions. To reduce these, we propose to triangulate the shapes’ parameterizations rather than the shapes themselves.
| Original language | English |
|---|---|
| Journal | Biomedizinische Technik |
| Volume | 57 |
| Issue number | SI-1 Track-B |
| Number of pages | 1 |
| ISSN | 0013-5585 |
| DOIs | |
| Publication status | Published - 01.01.2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 9 Industry, Innovation, and Infrastructure
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