Segmentation Techniques for Cardiovascular Modeling

A. A. Danilov, R. A. Pryamonosov and A. S. Yurova
Additional contact information
A. A. Danilov: Russian Academy of Sciences, Institute of Numerical Mathematics
R. A. Pryamonosov: Russian Academy of Sciences, Institute of Numerical Mathematics
A. S. Yurova: Russian Academy of Sciences, Institute of Numerical Mathematics

A chapter in Trends in Biomathematics: Modeling, Optimization and Computational Problems, 2018, pp 49-58 from Springer

Abstract: Abstract In this work we develop and present automatic and semi-automatic user-guided methods and algorithms for patient-specific image segmentation and generation of discrete geometric models for several cardiovascular biomedical applications. A new technique for dynamic heart ventricles segmentation and mesh generation using dynamic contrast enhanced Computed Tomography images is presented in detail.

Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-91092-5_4

Ordering information: This item can be ordered from
http://www.springer.com/9783319910925

DOI: 10.1007/978-3-319-91092-5_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().