| Title |
Computational fluid dynamics modelling and automatic classification of healthy human cerebral ventricular system components / |
| Authors |
Kaminskaitė, Greta ; Misiulis, Edgaras ; Ratkūnas, Vytenis ; Džiugys, Algis ; Skarbalius, Gediminas ; Navakas, Robertas |
| Full Text |
|
| Is Part of |
Absrract Book International Health Sciences Conference March 30-31 2023.. Kaunas : Students’ Scientific Society of Lithuanian University of Health Sciences. 2023, p. 76-78.. ISSN 2783-7408 |
| Abstract [eng] |
Nowadays, Computational Fluid Dynamics (CFD) is becoming a viable tool in applied medical research, including research on the dynamics of cerebrospinal fluid (CSF) flow in human cerebral ventricular system (CVS) and subarachnoid space (SAS). To analyse the CSF flow dynamics, a classification of the anatomical regions of CVS is needed. Manual classification of human CVS is an extremely time-consuming procedure. To make this classification faster, a few semi-automatic or automatic classification methods have been proposed, such as multi-atlas label fusion method [1-3] and methods that use deep neural network [4-6]. We propose a novel approach for automatic classification of human cerebral ventricles that is based on the numerical modelling of CSF flow through the CVS. |
| Published |
Kaunas : Students’ Scientific Society of Lithuanian University of Health Sciences |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2023 |
