1. TUHH Open Research (TORE)

I³-Lab - Modell-gestütztes maschinelles Lernen für die Weichgewebsmodellierung in der Medizin

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Projekt

Project Title
I³-Lab - Modell-gestütztes maschinelles Lernen für die Weichgewebsmodellierung in der Medizin
 
Institute
 
Principal Investigator
 
Status
Laufend
 
Duration
01-03-2019
-
31-07-2023
 
Funding Organization
 
Parent project
 

Publications
(All)

Results 1-5 of 5

Issue DateTitleTypeAuthor(s)
18-Sep-2021Fulltext availableOpen AccessPredictive constitutive modelling of arteries by deep learningArticleHolzapfel, Gerhard A. ; Linka, Kevin ; Sherifova, Selda ; Cyron, Christian J. 
215-Mar-2021Fulltext availableOpen AccessConstitutive artificial neural networks : a fast and general approach to predictive data-driven constitutive modeling by deep learningArticleLinka, Kevin ; Hillgärtner, Markus ; Abdolazizi, Kian Philipp ; Aydin, Roland C. ; Itskov, Mikhail ; Cyron, Christian J. 
325-Jan-2021Fulltext availableOpen AccessConcentration‐specific constitutive modeling of gelatin based on artificial neural networksChapter/Article (Proceedings)Abdolazizi, Kian Philipp ; Linka, Kevin ; Sprenger, Johanna ; Neidhardt, Maximilian ; Schlaefer, Alexander ; Cyron, Christian J. 
42021Identification of the concentration‐dependent viscoelastic constitutive parameters of gelatin by combining computational mechanics and machine learningArticleAbdolazizi, Kian Philipp ; Linka, Kevin ; Sprenger, Johanna ; Neidhardt, Maximilian ; Schlaefer, Alexander ; Cyron, Christian J. 
52021Tailored methods for segmentation of intravascular ultrasound images via convolutional neural networksChapter/Article (Proceedings)Bargsten, Lennart ; Riedl, Katharina A. ; Wissel, Tobias ; Brunner, Fabian J. ; Schaefers, Klaus ; Sprenger, Johanna ; Grass, Michael ; Seiffert, Moritz ; Blankenberg, Stefan ; Schlaefer, Alexander