DESIGN OF AUTOMATED AI ANALYSIS REPORT GENERATION ON DICOM SERVER FOR CHEST X-RAY (CXR) MEDICAL IMAGES

• Main Author: Daniel Reynardo Samosir, Arga
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/85907
• Institution: Institut Teknologi Bandung

Medical image analysis tasks are performed repeatedly, leading to fatigue and reduced capabilities of radiologists. The trend of radiological examinations continues to increase year by year, necessitating assistance for doctors in conducting analyses. This research applies the Design Science Research Methodology by developing a solution design to address the challenges faced by doctors in medical image analysis and testing this design against the needs of radiologists. The solution developed is an automation prototype to generate AI analysis reports in DICOM Structured Report (DICOM-SR) format on DICOM storage, specifically for chest X-ray (CXR) images. This prototype successfully automates the generation of AI analysis reports in DICOM Structured Report (DICOM-SR) format. Testing shows that analysis reports can be produced in less than 3 minutes and contain information on the type and details of diseases. Despite limitations such as system capabilities, inconsistent results, and clinical validation, this technology meets doctors' needs and has the potential to save time and improve the efficiency of radiology services.