Learning Application Model of Head CT Scan Image Evaluation for Health Human Resource Capacity Building - Saifudin, Saifudin; Setiawan, Agung Nugroho; Amalia, Rizki (SANITAS: Jurnal Teknologi dan Seni Kesehatan, 2024)
Background: CT image evaluation of head scan is one of the competencies in radiographic students including students in Radiographer education. Students must be able to analyze image quality, which includes anatomical criteria as well as diagnostic information of CT Scan images. This research is a pioneering effort to use AI in analyzing CT Scan images obtained retrospectively from Radiology Installations. Objective: the use of Artificial Intelligence as a learning application that can be utilized by radiography students in studying the accuracy of image intensity and automatic anatomical positioning in a head CT Scan Image analysis application. Method: The study used CT scan images that researchers collected and obtained retrospectively from the Radiology Installation. The use of Artificial Intelligence methods in accordance with the needs of research and development of Matlab Software is used in designing programs for applications. Results: In the aspect of object setting accuracy, the application can assess the accuracy of the position of the Head Object rotation or not and assess the intensity of the CT Scan image. The test accuracy value of this application is 97,78%, specificity is 100% and sensitivity is 94,45%. Conclusion: This application program can be used to increase the skills of radiographer students.