TY - GEN
T1 - A Virtual Reality Educational Tool for Complex Brain Anatomy
AU - Alhmoudi, Shaikhah
AU - Alkatheri, Sumyah
AU - Alghafri, Shamma
AU - Idrais, Abdel Rahman
AU - Damseh, Rafat
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Brain anatomy presents a unique pedagogical challenge in medical education due to its complex structures and the detailed intricacies inherent to various brain regions. Advanced imaging techniques such as computed tomography (CT), T1/T2 magnetic resonance imaging (MRI), and diffusion imaging provide 3D representations of these anatomical details, which require suitable tools and visualization setups to be taught efficiently to medical students. Machine learning and virtual reality have emerged as promising avenues for refining the visualization and reconstruction processes of these details. This paper delves into the integration of cutting-edge deep learning (DL) algorithms designed for the reconstruction of brain vascular trees and neural fiber tracts within an immersive virtual reality (VR) framework. Our proposed solution has the potential to improve brain anatomy education by serving as tool for illustrating subject-specific complex structures. The ensuing results underscore the viability and efficacy of our solution.
AB - Brain anatomy presents a unique pedagogical challenge in medical education due to its complex structures and the detailed intricacies inherent to various brain regions. Advanced imaging techniques such as computed tomography (CT), T1/T2 magnetic resonance imaging (MRI), and diffusion imaging provide 3D representations of these anatomical details, which require suitable tools and visualization setups to be taught efficiently to medical students. Machine learning and virtual reality have emerged as promising avenues for refining the visualization and reconstruction processes of these details. This paper delves into the integration of cutting-edge deep learning (DL) algorithms designed for the reconstruction of brain vascular trees and neural fiber tracts within an immersive virtual reality (VR) framework. Our proposed solution has the potential to improve brain anatomy education by serving as tool for illustrating subject-specific complex structures. The ensuing results underscore the viability and efficacy of our solution.
KW - artificial intelligence
KW - brain anatomy
KW - education
KW - virtual reality
UR - http://www.scopus.com/inward/record.url?scp=85180530494&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85180530494&partnerID=8YFLogxK
U2 - 10.1109/ICICS60529.2023.10330435
DO - 10.1109/ICICS60529.2023.10330435
M3 - Conference contribution
AN - SCOPUS:85180530494
T3 - 2023 14th International Conference on Information and Communication Systems, ICICS 2023
BT - 2023 14th International Conference on Information and Communication Systems, ICICS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th International Conference on Information and Communication Systems, ICICS 2023
Y2 - 21 November 2023 through 23 November 2023
ER -