VirtuScope: development of a high-fidelity virtual microscope simulation system for histology education
BACKGROUND: Microscope operation is a core skill in morphological laboratory education. However, traditional instructional approaches often face limitations in equipment accessibility, procedural guidance, and hands-on opportunities. With the advancement of virtual simulation technologies, new pathways have emerged for improving practical skill training. This study presents the development of VirtuScope, a high-fidelity virtual microscope simulation system, and explores its application value in histology education. METHODS: VirtuScope was developed as a standalone virtual simulation system for microscopes, featuring 1:1 3D structural reconstruction and high-fidelity simulation of physical interactions and optics, powered by advanced human-computer interaction and computer graphics. Key simulation features include focus adjustment, objective switching, and light source control. In the instructional design, VirtuScope was integrated into a blended teaching model combining video guidance, self-directed practice, and progressive transition to real microscope use. Student feedback and learning outcomes were evaluated using pre- and post-course questionnaires and knowledge tests. RESULTS: Students rated the system highly in terms of image clarity, interactivity, and instructional support. Most participants reported improved understanding of microscope structure and operation, and over 90% expressed willingness to use VirtuScope in future learning. Knowledge test scores showed significant post-course improvement (p < 0.001), and the overall recommendation rate reached 98.52%. CONCLUSION: VirtuScope demonstrates strong adaptability and educational support capacity. Its visual, interactive, and repeatable features enhance learning efficiency and practical competence, offering a scalable complement to traditional microscopy training. Moreover, it provides a feasible solution for institutions with limited laboratory resources, extending access to high-quality microscopy education across diverse learning environments.
Authors
- X Li
- Weixin Huang (ORCID: https://orcid.org/0000-0002-3278-4490)
- Jingyan Chen (ORCID: https://orcid.org/0000-0003-4174-0606)
- Xi Hang Cao (ORCID: https://orcid.org/0000-0002-2610-9712)
- Zhongjing Su
- Minwen Zhan
- Yuwei Lin
- Kaiqi Zhang
- Yang Gao
Institutions
- Shantou University (CN)
- Shantou University Medical College (CN)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2026-05-21
- DOI
- https://doi.org/10.1186/s12909-026-09416-z
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Basic and Applied Basic Research Foundation of Guangdong Province