Study Organisation and Teaching
The undergraduate professional study programme in Radiological Technology, lasting three years, educates highly competent healthcare professionals for work in medicine and related fields, including dentistry and veterinary medicine. Upon completion of the programme, students obtain the professional title Bachelor of Radiological Technology (baccalaureus) and acquire specific theoretical knowledge and practical skills that enable employment in hospital and non-hospital, public and private healthcare institutions.
The programme prepares students for work in three key areas of modern medicine: diagnostic and interventional radiology, radiotherapy and oncology, and nuclear medicine. Radiological technologists participate in all segments of radiological diagnostics, interventional procedures, and therapeutic processes, and as equal and indispensable members of multidisciplinary teams, they collaborate daily with specialists in radiology, radiotherapy and oncology, and nuclear medicine. In recent years, the demand for this profession has significantly increased in fields such as invasive cardiology, vascular surgery, and advanced diagnostics in dentistry and veterinary medicine, where the application of modern radiological diagnostic and interventional procedures has become standard practice.
The profession of a radiological technologist requires an exceptionally high level of expertise, responsibility, and professional accountability. During education and later professional work, they independently operate complex diagnostic and therapeutic equipment of high technological and financial value, while simultaneously implementing measures to protect patients, themselves, and other staff from unnecessary exposure to ionising radiation. This level of responsibility requires precision, maturity, ethical conduct, and a constant focus on patient safety.
Furthermore, since radiology, radiotherapy, and nuclear medicine are highly dynamic fields in terms of technological and methodological development, characterised by continuous innovation and rapid implementation of new technologies, there is a constant need for lifelong learning. Radiological technologists are expected to engage in continuous education, practical training, and active monitoring of modern professional and scientific advancements.
The study programme is therefore diverse, dynamic, and interdisciplinary. It integrates topics from medicine, technology, physics, and computer science, enabling students to acquire a broad range of professional competencies and to work independently and responsibly in modern healthcare systems.
Teaching is delivered through lectures, seminars, laboratory and clinical exercises, demonstrations, and continuous practical work in real clinical environments. Clinical training is organised at the teaching bases of the Clinical Hospital Centre Rijeka – at the Clinical Department of Diagnostic and Interventional Radiology, the Clinic for Radiotherapy and Oncology, and the Clinical Department of Nuclear Medicine – where students gain direct experience working with patients and state-of-the-art medical equipment.
For transparency and quality assurance, all courses, course coordinators, and syllabi are publicly available on the official faculty website, allowing students detailed insight into course content, learning outcomes, assessment methods, and grading systems.
At the end of the programme, students prepare and defend a final thesis, an independent professional work through which, under the supervision of a mentor, they demonstrate the ability to integrate knowledge, think critically, and solve practical problems in the field of radiological technology.
Department of Radiological Technology
Head of Department
- Prof. Melita Kukuljan, PhD, MD
- Office hours: Thursday 14:00–15:00, by prior email appointment, Clinical Department of Diagnostic and Interventional Radiology, Sušak location
- e-mail: melita.kukuljan@uniri.hr
Deputy Head of Department
- Senior Lecturer Maja Karić, BSc, MSc (Sanitary Administration)
- Office hours: Wednesday 14:00–15:00, by prior email appointment, Clinical Department of Diagnostic and Interventional Radiology, Rijeka location
- e-mail: maja.karic@uniri.hr
Administrative staff
- Sanja Sanković, MSc in Economics
- Tel.: +385 51 554 934
- e-mail: sanja.sankovic@uniri.hr
Staff
- Assist. Prof. Lovro Tkalčić, PhD, MD
- Office hours: Monday 14:00–15:00, by prior email appointment, Clinical Department of Diagnostic and Interventional Radiology, Sušak location
- e-mail: lovro.tkalcic@unir.hr
- Assoc. Prof. Neva Girotto, PhD, MD
- e-mail: neva.girotto@uniri.hr
- Lecturer Ena Mršić, MD
- e-mail: enamrsic94@gmail.com
External Associates (Title Holders)
- Assist. Prof. Klaudija Višković, PhD, MD
- e-mail: viskovick@gmail.com
- Assist. Prof. Marin Marinović, PhD, MD
- e-mail: marin.marinovic2@gmail.com
- Assist. Prof. Slavica Kovačić, PhD, MD
- e-mail: slavica.kovacic@yahoo.com
- Lecturer Boris Barać, BSc (Radiological Technology), MSc (Economics)
- e-mail: boris.barac@gmail.com
- Lecturer Karlo Blažetić, MSc (Bioinformatics)
- e-mail: karlo.blazetic@uniri.hr
- Lecturer Ivan Brumini, MD
- e-mail: brumini92@gmail.com
- Lecturer Andrej Požgaj, BSc (Radiological Technology)
- e-mail: pozgajandrej2@gmail.com
Publications (2021–2026)
- Samaržija M, Krpina K, Marušić A, Jakopović M, Aboud A, Kukuljan M, Šakić VA, Balint I, Kauczor HU, Yip R, Yankelevitz D, Henschke C. Design of the first national lung cancer screening program in the European Union: the Croatian model. Eur Radiol. 2025. doi:10.1007/s00330-025-12185-w
- Rončević Filipović M, Trobonjača Z, Cekinović Grbeša Đ, Filipović M, Kukuljan M, Mršić E, Tešić V, Živčić-Ćosić S. Outbreak of hantavirus disease caused by Puumala virus, Croatia, 2021. Euro Surveill. 2025;30(3):2400127. doi:10.2807/1560-7917.ES.2025.30.3.2400127
- Beck D, Balen Topić M, Višković K, Papić N, Žic R, Sviben M, Meštrović T, Baković Kovačević A, Beck R. Double trouble on the lower leg—unique human coinfection with Echinococcus granulosus and Echinococcus multilocularis without liver involvement. Pathogens. 2025;14(4):343. doi:10.3390/pathogens14040343
- Slivšek G, Mijač S, Dolanc I, Fabijanec M, Petković S, Mautner R, Lončarek K, Kranjčić J, Blagaić AB, Marinović M, Vitale K, Verbanac D, Čoklo M, Vraneković J. Oxidative stress and Down syndrome: a systematic review. Antioxidants (Basel). 2025;14(7):816. doi:10.3390/antiox14070816
- Markić D, Minić Ž, Šimičić J, Kuljanić K, Strčić J, Bonifačić D, Sušanj IM, Jakšić A, Sveško Visentin H, Ehrman R, Marinović M. On-line survey about autonomic dysreflexia in individuals with spinal cord injury in Croatia. J Clin Med. 2025;14(3):670. doi:10.3390/jcm14030670
- Kaštelan M, Brumini I, Poropat G, Tkalčić L, Grubešić T, Miletić D. Pancreatic iodine density and fat fraction on dual-energy computed tomography in acute pancreatitis. Diagnostics. 2024;14:955. doi:10.3390/diagnostics14090955
- Agarwal S, Saxena S, Carriero A, Chabert GL, Ravindran G, Paul S, Laird JR, Garg D, Fatemi M, Mohanty L, Dubey AK, Singh R, Fouda MM, Singh N, Naidu S, Višković K, Kukuljan M, Kalra MK, Saba L, Suri JS. COVLIAS 3.0: cloud-based quantized hybrid UNet3+ deep learning for COVID-19 lesion detection in lung computed tomography. Front Artif Intell. 2024;7:1304483
- Kukuljan M, Mršić E, Oštarijaš E. CT-guided transthoracic core needle biopsies of focal pleural lesions smaller than 10 mm: a retrospective study. Cancer Imaging. 2023;23(1):48
- Dubey AK, Chabert GL, Carriero A, Pasche A, Danna PSC, Agarwal S, Mohanty L, Nillmani, Sharma N, Yadav S, Jain A, Kumar A, Kalra MK, Sobel DW, Laird JR, Singh IM, Singh N, Tsoulfas G, Fouda MM, Alizad A, Kitas GD, Khanna NN, Višković K, Kukuljan M, Al-Maini M, El-Baz A, Saba L, Suri JS. Ensemble deep learning derived from transfer learning for classification of COVID-19 patients on hybrid deep-learning-based lung segmentation: a data augmentation and balancing framework. Diagnostics (Basel). 2023;13(11):1954
- Al-Maini M, Maindarkar M, Kitas GD, Khanna NN, Misra DP, Johri AM, Mantella L, Agarwal V, Sharma A, Singh IM, Tsoulfas G, Laird JR, Faa G, Teji J, Turk M, Višković K, Ruzsa Z, Mavrogeni S, Rathore V, Miner M, Kalra MK, Isenovic ER, Saba L, Fouda MM, Suri JS. Artificial intelligence–based preventive, personalized and precision medicine for cardiovascular disease/stroke risk assessment in rheumatoid arthritis patients: a narrative review. Rheumatol Int. 2023;43(11):1965–1982. doi:10.1007/s00296-023-05415-1
- Suri JS, Paul S, Maindarkar MA, Puvvula A, Saxena S, Saba L, Turk M, Laird JR, Khanna NN, Višković K, Singh IM, Kalra M, Krishnan PR, Johri A, Paraskevas KI. Cardiovascular/stroke risk stratification in Parkinson’s disease patients using atherosclerosis pathway and artificial intelligence paradigm: a systematic review. Metabolites. 2022;12(4):312. doi:10.3390/metabo12040312
- Suri JS, Maindarkar MA, Paul S, Ahluwalia P, Bhagawati M, Saba L, Faa G, Saxena S, Singh IM, Chadha PS, Turk M, Johri A, Khanna NN, Višković K, Mavrogeni S, Laird JR, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou AD, Misra DP, Agarwal V, Kitas GD, Kolluri R, Teji JS, Al-Maini M, Dhanjil SK, Sockalingam M, Saxena A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Omerzu T, Naidu S, Nicolaides A, Paraskevas KI, Kalra M, Ruzsa Z, Fouda MM. Deep learning paradigm for cardiovascular disease/stroke risk stratification in Parkinson’s disease affected by COVID-19: a narrative review. Diagnostics (Basel). 2022;12(7):1543. doi:10.3390/diagnostics12071543
- Savić Vuković A, Kukuljan M, Dinter M, Jurinović K, Jonjić N. The diagnostic challenge of adenocarcinoma in pulmonary nodular lymphoid hyperplasia. SAGE Open Med Case Rep. 2021;9:2050313X211039371. doi:10.1177/2050313X211039371
- Valković Zujić P, Božanić A, Jurković S, Šegota D, Grgurević Dujmić E, Čandrlić B, Karić M. The role of self-evaluation and education of radiographers involved in a breast cancer screening program at Clinical Hospital Center Rijeka. Radiography. 2021;27(4):1162–1165. doi:10.1016/j.radi.2021.06.007