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

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snapshot-2022-008.pdf

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snapshots: overview

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Mathematical subjects

Algebra and Number Theory
Analysis
Didactics and Education
Discrete Mathematics and Foundations
Geometry and Topology
Numerics and Scientific Computing
Probability Theory and Statistics

Connections to other fields

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

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