# An online training platform for SPECT imaging technology utilizing three-dimensional modeling

**Authors:** Lihua Qiao, Hongzhi Wang, Xiaorui Guo, Xinkun Lei, Hua Shang, Ruibin Zhao, Tian Xia, Ruiping Qin, Zikun Fang, Luqi Shou, Yiwen Qin, Dandan Shang, Alexandre Bonatto, Alexandre Bonatto, Alexandre Bonatto, Alexandre Bonatto, Alexandre Bonatto, Alexandre Bonatto

PMC · DOI: 10.1371/journal.pone.0323153 · PLOS One · 2026-02-12

## TL;DR

This paper introduces an online SPECT imaging training platform using 3D modeling to address challenges in nuclear medicine education.

## Contribution

A novel online training platform for SPECT imaging using 3D modeling and interactive modules to support personalized medical education.

## Key findings

- The platform includes six 3D scene modules and seven disease examination processes for interactive learning.
- Training data shows a normal score distribution and positive feedback from frequent training sessions.
- The platform has been adopted in multiple institutions and supports personalized training and early clinical thinking.

## Abstract

The provision of nuclear medicine experimental classes within universities poses significant challenges due to the high risk, substantial cost, and large size of the requisite equipment. To address the bespoke training needs of students majoring in imaging technology in this new medical era, our team has developed an online training platform specifically for SPECT imaging technology, a key aspect of nuclear medicine.

This platform utilises advanced technologies such as Unity3D to create six three-dimensional scene modules of SPECT imaging and seven typical disease examination operation processes. As a result, we have achieved a human-computer interactive three-dimensional virtual system. The aforementioned teaching strategy has been implemented in our institution’s instructional practice across five semesters, in addition to being adopted by three other medical colleges.

Training data reveals that the overall sample score distribution aligns with a normal distribution, suggesting that the platform’s structure is logically and effectively designed. Furthermore, the linear fit slopes of individual sample scores are consistently positive, indicating that the frequency of training sessions yields a positive feedback effect on students’ bespoke training. The innovative nature of this platform is protected through computer software copyrights.

Our online training platform enhances course structure and student training objectives, effectively accommodating the requirements of nuclear medicine teaching for personalized student training, innovative thinking, and the “early clinical” mindset.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

15 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12900319/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12900319/full.md

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Source: https://tomesphere.com/paper/PMC12900319