• Automated Prediction of Fractional Flow Reserve through Numerical Simulation of Coronary Artery Flow 

      Magnus Johannesen (Master thesis, 2019)
      I denne masteroppgaven har det blitt utviklet en metode for å bestemme "Fractional Flow Reserve" indeksen for kvantifisering av funksjonell reduksjon i menneskelige kransarterier. Metoden har benyttet seg av den ...
    • Comparison of numerical schemes for nonlinear 1-D arterial blood flow modeling 

      Fossan, Fredrik Eikeland (Master thesis, 2015)
      In this Thesis, the numerical methods used in STARFiSh (MacCormack or McC) have been tested and compared with five other state of the art flow-solvers: discontinuous Galerkin (DCG), locally conservative Galerkin (LCG), ...
    • Effect of side branch flow upon physiological indices in coronary artery disease 

      Gosling, Rebecca C.; Sturdy, Jacob; Morris, Paul D.; Fossan, Fredrik Eikeland; Hellevik, Leif Rune; Lawford, Patricia V.; Hose, David Rodney; Gunn, Julian P. (Peer reviewed; Journal article, 2020)
      Recent efforts have demonstrated the ability of computational models to predict fractional flow reserve from coronary artery imaging without the need for invasive instrumentation. However, these models include only larger ...
    • Impact of baseline coronary flow and its distribution on Fractional Flow Reserve prediction 

      Muller, Lucas Omar; Fossan, Fredrik Eikeland; Bråten, Anders Tjellaug; Jørgensen, Arve; Wiseth, Rune; Hellevik, Leif Rune (Journal article; Peer reviewed, 2019)
      Model‐based prediction of fractional flow reserve (FFR) in the context of stable coronary artery disease (CAD) diagnosis requires a number of modelling assumptions. One of these assumptions is the definition of a baseline ...
    • Machine learning augmented reduced-order models for FFR-prediction 

      Fossan, Fredrik Eikeland; Müller, Lucas O.; Sturdy, Jacob; Bråten, Anders Tjellaug; Jørgensen, Arve; Wiseth, Rune; Hellevik, Leif Rune (Peer reviewed; Journal article, 2021)
      Computational predictions in cardiovascular medicine have largely relied on explicit models derived from physical and physiological principles. Recently, the application of artificial intelligence in cardiovascular medicine ...
    • Optimization of topological complexity for one-dimensional arterial blood flow models 

      Fossan, Fredrik Eikeland; Mariscal-Harana, Jorge; Alastruey, Jordi; Hellevik, Leif Rune (Journal article; Peer reviewed, 2018)
      As computational models of the cardiovascular system are applied in modern personalized medicine, maximizing certainty of model input becomes crucial. A model with a high number of arterial segments results in a more ...
    • Physics-based and data-driven reduced order models: applications to coronary artery disease diagnostics 

      Fossan, Fredrik Eikeland (Doctoral theses at NTNU;2020:362, Doctoral thesis, 2020)
      In this thesis we have developed reduced-order models for the prediction of pressure and flow in the arterial system and for the diagnosis of coronary artery disease. By reduced-order model we refer to a reduction of ...
    • Segmentation of Coronary Arteries using Transformers 

      Larsen, Michael Staff (Master thesis, 2023)
      Koronar hjertesykdom (CAD) er en betydelig helseutfordring på verdensbasis. Tilstanden diagnostiseres tradisjonelt med invasive, kostbare metoder som Invasive Coronary Angiography (ICA) og invasive Fractional Flow Reserve ...
    • Uncertainty quantification and sensitivity analysis for computational FFR estimation in stable coronary artery disease 

      Fossan, Fredrik Eikeland; Sturdy, Jacob; Muller, Lucas Omar; Strand, Andreas; Bråten, Anders Tjellaug; Jørgensen, Arve; Wiseth, Rune; Hellevik, Leif Rune (Journal article; Peer reviewed, 2018)
      Purpose The main objectives of this study are to validate a reduced-order model for the estimation of the fractional flow reserve (FFR) index based on blood flow simulations that incorporate clinical imaging and ...