COMPUTER GRAPHICS-BASED SYSTEM FOR VISUAL DIAGNOSIS OF MEDICAL DATA
Keywords:
Medical Imaging, 3D Visualization, Computer-Aided Diagnosis, Image Segmentation, Clinical Decision Support, Augmented Reality, Digital Diagnostics, Human-Computer Interaction, Diagnostic Accuracy, Visual AnalyticsAbstract
The increasing volume and complexity of medical imaging data from CT, MRI, and PET pose challenges for accurate and efficient diagnosis. This study presents an integrated visual diagnostic system based on computer graphics principles. The system consists of three modules: data processing for image standardization and segmentation, visualization for interactive 2D/3D modeling using the Marching Cubes algorithm, and an interactive communication module supporting VR/AR interfaces. The system was evaluated on 450 retrospective images from public (TCIA) and local datasets focusing on breast and liver pathologies. The results showed a tumor detection precision of 93.5% and sensitivity of 90.8%. A user study involving ten clinicians demonstrated a 40% reduction in diagnostic time and confirmed the system’s effectiveness in understanding complex anatomical relationships, particularly for surgical planning. The findings indicate that computer graphics–based visual diagnostic systems can significantly enhance diagnostic accuracy, efficiency, and clinical communication.
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