Sergios Gatidis

Professor Sergios Gatidis is making strides in research on multiparametric oncologic medical imaging, with a particular focus on hybrid imaging and the integration of machine learning for medical image analysis. As an Associate Professor of Radiology, specializing in Pediatric Radiology, at Stanford Medicine, he brings a unique blend of expertise in both medicine and mathematics to his work. Dr. Gatidis received his medical training from the University of Tuebingen in Germany, where he developed a strong foundation in clinical radiology. Complementing his medical expertise, he also holds a Diploma in Mathematics from the Universities of Tuebingen and Hagen, Germany. This dual background enables him to approach complex imaging challenges with a comprehensive analytical perspective. His research is centered on advancing the field of oncologic imaging by developing innovative techniques that enhance the accuracy and efficiency of cancer diagnosis and treatment monitoring. By leveraging machine learning, Dr. Gatidis aims to improve the interpretation of medical images, making them more informative and actionable for clinicians. At Stanford, Professor Gatidis is actively involved in collaborative projects that push the boundaries of medical imaging technology. His work not only contributes to the academic community but also has a significant impact on patient care, particularly in the realm of pediatric radiology. Through his dedication and pioneering research, he continues to shape the future of medical imaging.