AI Fellowship at TUHH: Medical Imaging and Innovation
Meet Žygimantas Skučas, a third-year medical student from the Lithuanian University of Health Sciences, who recently completed a research fellowship at the Hamburg University of Technology (TUHH) as part of the SustAInLivWork International Internship Programme. With a growing interest in radiology, cardiac surgery, and orthopaedics, Žygimantas is passionate about exploring how AI and advanced imaging technologies can support innovation in medicine.
From Radiology Internships to International AI Research
Before applying for the TUHH fellowship, Žygimantas had already completed several internships in radiology clinics and was preparing for an upcoming cardiac surgery internship in France. During a project within the SustAInLivWork team, where he contributed to annotating coronary artery images for AI training, he discovered the opportunity to further explore AI in medicine through the TUHH internship.
“The work I did annotating atherosclerotic plaques to train AI models gave me a real glimpse into how data and technology can come together in modern diagnostics. That’s when I learned about the TUHH opportunity.”
Exploring Vascular Modelling and Imaging Technologies
At TUHH, Žygimantas worked with ultrasound and optical coherence tomography (OCT) technologies. OCT, in particular, caught his attention as a powerful and innovative diagnostic tool. He took part in creating a variety of vascular models simulating real pathological changes, including atherosclerotic plaques, stenosis, thrombosis, inflammation, and fibrosis.
Additionally, he contributed to shear wave elastography research, developing gelatin-based models with different shaped inclusions to imitate tissue echogenicity. He got an opportunity to conduct experiments analysing how different materials and barriers influence wave propagation.
Gaining Practical Skills and Insights
The fellowship provided not only hands-on laboratory experience but also enhanced his understanding of AI applications in medicine. Žygimantas learned to process and analyse imaging data using specialised software, interpreted OCT scans, and worked with elastography datasets. Importantly, the internship helped him improve his communication skills in English and become more confident in both independent and team-based research settings.
“This experience strengthened my motivation to pursue innovations in medicine, especially in radiology. Knowing how AI works and what data it needs is relevant to almost any field in healthcare.”
Žygimantas sees this fellowship as a key stepping stone in his academic journey. Exposure to advanced diagnostic technologies and modelling practices will benefit his future studies and professional ambitions, particularly in the medical imaging domain.
To students thinking about applying for similar programmes, Žygimantas says: “Don’t be afraid to take on new challenges. Opportunities like these let you grow both professionally and personally. Be proactive, connect with your lecturers and peers, and take every chance to gain international experience – it can really shape your career path.”