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Titel:

Probabilistic noninvasive prediction of wall properties of abdominal aortic aneurysms using Bayesian regression.

Dokumenttyp:
Journal Article
Autor(en):
Biehler, Jonas; Kehl, Sebastian; Gee, Michael W; Schmies, Fadwa; Pelisek, Jaroslav; Maier, Andreas; Reeps, Christian; Eckstein, Hans-Henning; Wall, Wolfgang A
Abstract:
Multiple patient-specific parameters, such as wall thickness, wall strength, and constitutive properties, are required for the computational assessment of abdominal aortic aneurysm (AAA) rupture risk. Unfortunately, many of these quantities are not easily accessible and could only be determined by invasive procedures, rendering a computational rupture risk assessment obsolete. This study investigates two different approaches to predict these quantities using regression models in combination with...     »
Zeitschriftentitel:
Biomech Model Mechanobiol
Jahr:
2017
Band / Volume:
16
Heft / Issue:
1
Seitenangaben Beitrag:
45-61
Sprache:
eng
Volltext / DOI:
doi:10.1007/s10237-016-0801-6
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/27260299
Print-ISSN:
1617-7959
TUM Einrichtung:
Fachgebiet Gefäßchirurgie (Prof. Eckstein)
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