3D Virtual Brain Simulation Teaching Platform
Xuanqi Zhang, Weihao Yue, Junyi Chen, Xinyang Li, Yamei Luo, Lisha Zhong
ABSTRACT
To address limitations in traditional cerebral anatomy education — such as limited specimen availability, low interactivity, and poor learning retention—a browser–server (B/S)–based 3D virtual simulation teaching platform has been developed. Integrating 3D Slicer for image segmentation, Blender for anatomical modeling, and the Unity 3D engine for real-time rendering and interaction, the platform is composed of three functional modules: Anatomical Cognition, Functional Correlation, and Clinical Cases. Users can explore multimodal brain structures, simulate CT slice navigation, visualize dynamic pathological processes, and engage with an AI-assisted tutor for real- time feedback. The backend system, built with Python and MySQL, supports personalized learning through practice- test modules and data-driven learning analytics, enabling individualized performance tracking and adaptive learning pathways. Compared with conventional instruction, the platform has been shown to increase student engagement by over 85% and improve knowledge retention by more than 30%. Its versatility also supports broader applications in continuing medical education, science communication, and remote instruction. By overcoming the constraints of traditional anatomical teaching, this 3D virtual platform presents a scalable, intelligent, and immersive solution for innovating medical education and promoting equitable access to high-quality teaching resources. physical equipment and specimens, offering a new path for