Design and Development of an Intelligent Visualization System Platform for Medical Imaging

Abstract

This paper presents an intelligent visualization learning platform centered on medical imaging education. The platform integrates
modern technologies with the needs of medical education, designing five core functional modules: theoretical learning, a question-answering
module, a knowledge network graph, pain assessment training, and a mixed reality (MR) interface. The theoretical learning module supports
text size and background adjustments, video annotation, equipment observation, and text note-taking features, aiming to enhance personalized
learning experiences for students. The question-answering module allows customization of question ranges, difficulty levels, and timing functions, helping students strengthen their practice and mark challenging questions for focused review. The knowledge network graph dynamically calculates learning progress and generates learning reports, enabling students to systematically grasp key knowledge points. The pain
assessment training module utilizes virtual medical imaging and simulated consultations to improve diagnostic skills while supporting levelbased evaluation training based on image analysis. The mixed reality module employs MR technology to facilitate equipment disassembly,
pathological explanations, and anatomical learning, enhancing students' immersive experiences. Through user registration and data management functions, the system ensures the traceability of learning processes and personalized record-keeping, while dynamic data adaptation and
SQL storage enhance interactivity and efficiency. The platform's design provides an intelligent and systematic solution for medical imaging
education, offering innovative support for the integration of medical education and practical training.