Marina Codari

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About

Marina Codari is a leading researcher in medical imaging and radiology, with a primary focus on the application of artificial intelligence and deep learning to improve diagnostic accuracy. Her major contributions center on the automated segmentation and volumetric analysis of anatomical structures from CT and MRI scans, particularly within the head and neck region. Her most-cited work, "Volumetric assessment of sphenoid sinuses through segmentation on CT scan" (2017, 66 citations), established a foundational method for precise, reproducible sinus volume measurement, directly impacting surgical planning for endoscopic procedures. Beyond this, Codari has advanced the field by developing AI-driven tools for bone age assessment, osteoporosis screening, and cardiovascular risk prediction, demonstrating the broad clinical utility of quantitative imaging biomarkers. Her research has been instrumental in bridging the gap between computational algorithms and routine clinical practice, with her papers collectively amassing hundreds of citations. Recognized for her innovative work, she has contributed to major international radiology conferences and collaborative studies, solidifying her reputation as a key figure in the integration of machine learning into modern diagnostic radiology.