Medical imaging teaching is an image-based subject. During the learning process, students can improve their professional ability and ability to analyze and solve problems by analyzing and studying a large number of medical images. However, due to the limitation of medical imaging teaching resources in China, there are still problems in the teaching of medical imaging such as outdated teaching facilities, backward teaching models, and lack of practical experience for students. The components of the medical imaging teaching system in this study included the equipment for data acquisition, data storage, data processing, and teaching interactive. The Internet of Things (Iot) and artificial intelligence technology were integrated into the medical imaging teaching process to build a medical imaging recognition system. To help students better identify some images and integrate medical images with their own professional knowledge could promote the further development of medical image teaching. In order to verify the effectiveness of the model, 200 medical students from Guangxi University (Nanning, Guangxi, China) were included and divided into the experimental and the control groups. After learning the same contents in different learning formats, the performance of the experimental group that used the image library was found to be significantly better than that of the control group that used traditional teaching method. The results found that the AI and IoT-based medical imaging learning platform could help medical imaging teachers and students to obtain more medical imaging data and improve the utilization and sharing of teaching resources. It could also realize intelligent analysis of medical images to assist teachers in tasks such as diagnosis, segmentation, and classification, which could improve teaching efficiency and accuracy. Further, it could provide more application scenarios and cases for medical imaging teaching, expanded teaching contents and vision, and enhanced the relevance and practicality of teaching. © (2023). All Rights Reserved.
