Andreas Østvik

Andreas Østvik is a Researcher at the Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), financed by the Liaison Committee between Central Norway Regional Health Authority and NTNU. His work focuses on developing AI-driven methods for analyzing medical images, particularly in cardiac ultrasound (echocardiography), to improve diagnostic tools and clinical workflows. He holds a PhD in automatic analysis in echocardiography using machine learning and an MSc in physics/mathematics with biophysics and medical technology specialization.

Research Background: Østvik's research integrates deep learning with medical imaging, addressing challenges in cardiac imaging such as automated segmentation, strain analysis, and real-time guidance for standard echocardiography views. He also collaborates with SINTEF Digital's Health Research Department, advancing robotics and autonomy in medical interventions.

Key Contributions: His work includes developing tools like Annotation Web for ultrasound image annotation, improving reproducibility of strain measurements via deep learning, and validating AI models for left ventricular volumetrics. He has published extensively in journals like Ultrasound in Medicine and Biology, European Heart Journal, and IEEE transactions.

Affiliations: Active at AHL-senteret (Øya), he bridges academic and clinical research, emphasizing translational AI applications in cardiology. His projects aim to enhance diagnostic accuracy, reduce variability, and streamline echocardiography workflows.