Abstract
Mathematical and computational modeling of the cardiovascular system is increasingly providing non-invasive alternatives to traditional invasive clinical procedures.
Moreover, it has the potential for generating additional diagnostic markers.
In blood flow computations, the personalization of spatially distributed (i.e., 3D)
models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature.
In the last years, the development and application of inverse methods has rapidly expanded, most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decade
Moreover, it has the potential for generating additional diagnostic markers.
In blood flow computations, the personalization of spatially distributed (i.e., 3D)
models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature.
In the last years, the development and application of inverse methods has rapidly expanded, most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decade
| Original language | English |
|---|---|
| Article number | e3613 |
| Number of pages | 42 |
| Journal | Int J Numer Method Biomed Eng |
| Volume | 38 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - Aug-2022 |
Keywords
- blood flows
- inverse problems
- mathematical modeling
- medical imaging