Design and Evaluation of Clinical Medicine Teaching and Simulation Training Models Based on Mixed Reality Technology

Abstract

Abstract The purpose of exploring the application of mixed reality technology in clinical medicine teaching is to enhance the learning effect in clinical teaching. This paper utilizes the mixed reality technology framework to create a scene for clinical medicine teaching and simulation training and defines the interaction and teaching process for clinical medicine teaching simulation training. Based on the CT/MRI images of patients, the neural radiation field algorithm is combined to reconstruct the 3D model in the clinical medicine simulation scene, the Laplacian edge detection operator is used to preprocess the images, and the probabilistic-based importance sampling strategy is introduced to ensure the accuracy of the 3D reconstruction model. A comparative clinical medicine teaching experiment was designed to evaluate the teaching effect of the simulation training model with students from TR Hospital. The lowest ATE value of the 3D model obtained by the NeRF algorithm was only 0.011, while the result of the importance sampling strategy improved the PSNR value by 6.17% compared with that of the uniform sampling. The learning interest of the students in the observation group increased from 71.06±0.57 points before the experiment to 96.53±0.21 points after the experiment, and the 3D stereoscopic sense of the students in the observation group improved by 32.38% compared to the students in the control group. It is highly feasible to construct clinical medical simulation teaching based on mixed reality technology, which can improve students’ theoretical knowledge and practical skills in clinical medicine while effectively enhancing their learning interests.