Computational system for identifying sinusitis in Computed Tomography (CT) scans (Research, Society and Development, 2025)
Introduction: Sinusitis is an inflammation of the paranasal sinuses, with high incidence and potential complications when associated with other respiratory diseases. During the Covid-19 pandemic, case numbers decreased but lethality increased. Pollution, especially in industrial areas, exacerbates the incidence. Objective: To develop advanced imaging techniques to improve sinusitis diagnosis through the analysis of computed tomography scans. Methods: Application of artificial intelligence, particularly Machine Learning, and object detection techniques to identify structural changes in axial computed tomography images of the paranasal sinuses. Expected Results: Faster and more accurate diagnosis, contributing to the optimization of the diagnostic process and reduction of associated clinical complications. Conclusion: AI-based methods represent an important tool to enhance sinusitis diagnosis, enabling early interventions and better clinical management.