No abstract

No abstract

Aneurysms are one of the most common unexplored causes of death. There are many studies conducted by scientists around the world on this issue. The main problem raised is the cause of aneurysms. Here, the division includes several branches, i.e. genetic conditions, lifestyle, eg. smoking, and finally hemodynamic factors of blood flow. It is well known that the aneurysm is formed and ruptured at the site of high wall shear stress (WSS). This paper presents the comparison of results of CFD blood flow simulations with experimental values obtained with the Particle Image Velocimetry (PIV) method in a 3D model of a cerebral aneurysm. A 3D model of a cerebral aneurysm was developed using specific patient CT data. The hemodynamical parameters were analysed for different flow rates in a 3D model under pulsatile flow conditions. The CFD simulation was done using Ansys CFX software. Results of the simulation were validated with the experimental PIV method. Two different PIV methods were employed: traditional PIV based on cross-correlation (CC) algorithms and Artificial Intelligence PIV (AI PIV) based on Deep Learning and Convolutional Neural Networks. The obtained results showed a better correlation between CFD simulation and types of PIV analysis for data of AI PIV, which allows for a much higher spatial resolution of the resulting velocity field. Analysis of the results was promising and showed that AI PIV could be used to get accurate results.

BioOne Complete (complete.BioOne.org) is a full-text database of 200 subscribed and open-access titles in the biological, ecological, and environmental sciences published by nonprofit societies, associations, museums, institutions, and presses.