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Biological Shape Analysis with Geometric Statistics and Learning

Snapshots of modern mathematics from Oberwolfach

Biological Shape Analysis with Geometric Statistics and Learning

The advances in biomedical imaging techniques have enabled us to access the 3D shapes of a variety of structures: organs, cells, proteins. Since biological shapes are related to physiological functions, shape data may hold the key to unlocking outstanding mysteries in biomedicine. This snapshot introduces the mathematical framework of geometric statistics and learning and its applications to biomedicine.

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Mathematical subjects

Geometry and Topology
Probability Theory and Statistics

Connections to other fields

Computer Science
Life Science

Author(s)

Saiteja Utpala, Nina Miolane

License

DOI (Digital Object Identifier)

10.14760/SNAP-2022-008-EN

Download PDF

snapshot-2022-008.pdf

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snapshots: overview

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      Mathematical subjects

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      Connections to other fields

      Chemistry and Earth Science
      Computer Science
      Engineering and Technology
      Finance
      Humanities and Social Sciences
      Life Science
      Physics
      Reflections on Mathematics

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