TY  - JOUR
VL  - 875
SP  - 193
EP  - 209
ID  - scholars14027
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076848447&doi=10.1007%2f978-3-030-35252-3_10&partnerID=40&md5=24c604c5041fa20375b6ecc99123ef0e
N2  - Currently, medical scans yield large 3D data volumes. To analyze the data, image processing techniques are worth employing. Also, the data could be visualized to offer non-invasive and accurate 3D anatomical views regarding the inside of patients. Through this visualization approach, several medical processes or healthcare diagnostic procedures (including virtual reality (VR) aided operations) can be supported. The main aim of this study has been to discuss and provide a critical review of some of the recent scholarly insights surrounding the subject of CFD simulations with applications of VR-aided health care diagnostics. The studyâ??s specific objective has been to unearth how CFD simulations have been applied to different areas of health care diagnostics, with VR environments on the focus. Some of the VR-based health care areas that CFD simulations have been observed to gain increasing application include medical device performance and diseases or health conditions such as colorectal cancer, cancer of the liver, and heart failure. From the review, an emerging theme is that CFD simulations form a promising path whereby they sensitize VR operators in health care regarding some of the best paths that are worth taking to minimize patient harm or risk. Hence, CFD simulations have paved the way for VR operators to make more informed and accurate decisions regarding disease diagnosis and treatment tailoring relative to the needs and conditions with which patients present. © Springer Nature Switzerland AG 2020.
SN  - 1860949X
JF  - Studies in Computational Intelligence
N1  - cited By 4
AV  - none
PB  - Springer
A1  - Panwar, V.
A1  - Vandrangi, S.K.
A1  - Emani, S.
A1  - Velidi, G.
A1  - Hamza, J.
TI  - Computational fluid dynamics simulations with applications in virtual reality aided health care diagnostics
Y1  - 2020///
ER  -