Development of Computed Tomography Quality Control Training Application Model Based on the American College of Radiology Phantom Integrated Website

The use of Viewdex as a radiographic image evaluation tool has limited flexibility for students, especially in the complicated process of installation and input of DICOM ACR image results. These limitations can slow down the learning process and reduce the effectiveness of education on radiological image evaluation. This research aims to develop a web-integrated ACR Phantom-based CT quality control training application, which can overcome the weaknesses of Viewdex and improve efficiency and user experience. The research method used is Research and Development (R&D), which consists of several stages: literature study, product development, field testing, evaluation, and product revision. The application developed simplifies the process of DICOM data import, question coding, and automatic evaluation, improving operational efficiency. Validation of information technology and QA/QC experts shows that the application meets high standards in various aspects with 100% validity. Performance evaluation through pre-test and post-test showed a significant improvement in participants' knowledge and skills, with the Wilcoxon test showing a p-value of 0.005. The developed application has proven to be effective and efficient in improving the usability and learning experience of students, overcoming the weaknesses of Viewdex. Its advanced features enable efficient storage, retrieval, and management of medical images, as well as access and analysis of medical data.