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The Biomedical Imaging Research Group is dedicated to advancing innovative computational methods to enhance diagnostic accuracy. The group focuses on application of existing and developing new methods based on machine learning, signal processing, and image analysis algorithms. We analyze different modalities of data and work with different medical imaging data, i.e. MRI, CT, ultrasound, and optical imaging. By fostering interdisciplinary collaboration among clinicians, engineers, and scientists, the group translates research findings into practical clinical applications, improving disease detection, monitoring, and treatment strategies.
The Biomedical Imaging Research Group is dedicated to advancing innovative computational methods to enhance diagnostic accuracy. The group focuses on application of existing and developing new methods based on machine learning, signal processing, and image analysis algorithms. We analyze different modalities of data and work with different medical imaging data, i.e. MRI, CT, ultrasound, and optical imaging. By fostering interdisciplinary collaboration among clinicians, engineers, and scientists, the group translates research findings into practical clinical applications, improving disease detection, monitoring, and treatment strategies.
Below, you will find our list of publications and detailed profiles of our team members, complete with their biographies and the personal motivations that inspired them to join this research group.
Below, you will find our list of publications and detailed profiles of our team members, complete with their biographies and the personal motivations that inspired them to join this research group.
Merjem Bećirović
About: I am a final-year Master's student at the Faculty of Electrical Engineering, Department of Computing and Informatics, University of Sarajevo. My curiosity about "how things work" has driven me to pursue engineering, where I continuously find answers to my questions and uncover new ones to explore. While my interests span several fields, I have recently focused on the applications of AI in medical imaging, as well as cloud computing and security. Currently, I serve as a student teaching assistant at my faculty. I am excited about combining research with industry experience as I move forward in my career.
Merjem Bećirović
About: I am a final-year Master's student at the Faculty of Electrical Engineering, Department of Computing and Informatics, University of Sarajevo. My curiosity about "how things work" has driven me to pursue engineering, where I continuously find answers to my questions and uncover new ones to explore. While my interests span several fields, I have recently focused on the applications of AI in medical imaging, as well as cloud computing and security. Currently, I serve as a student teaching assistant at my faculty. I am excited about combining research with industry experience as I move forward in my career.
Motivation for joining: Seeing how algorithms can extract meaningful insights from complex medical images and help solve practical problems has sparked my desire to focus on this field of research over the past few years.
Motivation for joining: Seeing how algorithms can extract meaningful insights from complex medical images and help solve practical problems has sparked my desire to focus on this field of research over the past few years.
Amina Kurtović
About: I am a Bachelor of Computer Science and Informatics, currently pursuing my Master’s degree at the Faculty of Electrical Engineering, University of Sarajevo. My academic journey began with a dual high school education, as I successfully completed both the Second Gymnasium Sarajevo and the Music High School Sarajevo (2016–2020), demonstrating strong organizational and time management skills.
Amina Kurtović
About: I am a Bachelor of Computer Science and Informatics, currently pursuing my Master’s degree at the Faculty of Electrical Engineering, University of Sarajevo. My academic journey began with a dual high school education, as I successfully completed both the Second Gymnasium Sarajevo and the Music High School Sarajevo (2016–2020), demonstrating strong organizational and time management skills.
Passionate about continuous learning, I am always eager to expand my skill set, take on new challenges, and grow both technically and professionally. I have gained hands-on experience as a Junior Full Stack Developer and as a Student Teaching Assistant. Additionally, I have worked as a teacher at the Third Gymnasium Sarajevo, where I taught Informatics and Mobile Application Development.
Passionate about continuous learning, I am always eager to expand my skill set, take on new challenges, and grow both technically and professionally. I have gained hands-on experience as a Junior Full Stack Developer and as a Student Teaching Assistant. Additionally, I have worked as a teacher at the Third Gymnasium Sarajevo, where I taught Informatics and Mobile Application Development.
Motivation for joining: I first heard about the Biomedical Imaging group at the Faculty of Electrical Engineering from a friend. Realizing the quality of the people working in the team, I was eager to become a part of it. I am fascinated by how many valuable solutions can be created when AI and medicine are combined, and I would love to contribute to this field.
Motivation for joining: I first heard about the Biomedical Imaging group at the Faculty of Electrical Engineering from a friend. Realizing the quality of the people working in the team, I was eager to become a part of it. I am fascinated by how many valuable solutions can be created when AI and medicine are combined, and I would love to contribute to this field.
Elma Kandić
About: Elma Kandić is a master's student in biomedical engineering, with a background in automatic control and electronics. Elma has extensive experience in ECG signal analysis, fMRI interpretation, and deep learning applications in medical image processing. Currently, she is conducting her master's thesis in collaboration with the Karlsruhe Institute of Technology, Germany, aiming to improve the precision and efficiency of pulsed field ablation procedures by developing computational models that simulate electroporation dynamics in cardiac tissue. In her free time, she enjoys rollerblading—so if anyone shares the same passion, she’s always up for a challenge!
Elma Kandić
About: Elma Kandić is a master's student in biomedical engineering, with a background in automatic control and electronics. Elma has extensive experience in ECG signal analysis, fMRI interpretation, and deep learning applications in medical image processing. Currently, she is conducting her master's thesis in collaboration with the Karlsruhe Institute of Technology, Germany, aiming to improve the precision and efficiency of pulsed field ablation procedures by developing computational models that simulate electroporation dynamics in cardiac tissue. In her free time, she enjoys rollerblading—so if anyone shares the same passion, she’s always up for a challenge!
Motivation for joining: Through continuous learning, experimentation, and teamwork, I’m driven by the desire to unlock the full potential of medical imaging and make a real impact on healthcare. A medical image truly speaks louder than a thousand words!
Motivation for joining: Through continuous learning, experimentation, and teamwork, I’m driven by the desire to unlock the full potential of medical imaging and make a real impact on healthcare. A medical image truly speaks louder than a thousand words!
Stefani Kecman
About: I have completed my Bachelor's studies in the department of Computing and Informatics at the Faculty of Electrical Engineering, University of Sarajevo. During my Bachelor's studies, I worked as a student demonstrator on the courses: Mathematical Logic and Computability, Foundations of Computer Networks and Digital Signal Processing. Currently, I am enrolled as a MSc Computer Science student at the Albert-Ludwigs-University in Freiburg, Germany, specializing in Artificial Intelligence. I worked on projects dealing with autonomous navigation and reinforcement learning (as a part of my Bachelor's thesis), computer vision applications in plant phenotyping (in partnership with La Trobe University in Australia) and in solar physics (at the Institute for Solar Physics KIS - Freiburg). I am passionate about interdisciplinary applications of deep learning and computer vision. Furthermore, I am a member of the Association for the Advancement of Science and Technology (ANNT) BiH, where I participate in the projects of the BH Academic Directory and the Project of Student Research (PSI). More info: https://www.linkedin.com/in/stefani-kecman-33b3a127b/ and https://scholar.google.com/citations?user=6R7OXr0AAAAJ&hl=en
Stefani Kecman
About: I have completed my Bachelor's studies in the department of Computing and Informatics at the Faculty of Electrical Engineering, University of Sarajevo. During my Bachelor's studies, I worked as a student demonstrator on the courses: Mathematical Logic and Computability, Foundations of Computer Networks and Digital Signal Processing. Currently, I am enrolled as a MSc Computer Science student at the Albert-Ludwigs-University in Freiburg, Germany, specializing in Artificial Intelligence. I worked on projects dealing with autonomous navigation and reinforcement learning (as a part of my Bachelor's thesis), computer vision applications in plant phenotyping (in partnership with La Trobe University in Australia) and in solar physics (at the Institute for Solar Physics KIS - Freiburg). I am passionate about interdisciplinary applications of deep learning and computer vision. Furthermore, I am a member of the Association for the Advancement of Science and Technology (ANNT) BiH, where I participate in the projects of the BH Academic Directory and the Project of Student Research (PSI). More info: https://www.linkedin.com/in/stefani-kecman-33b3a127b/ and https://scholar.google.com/citations?user=6R7OXr0AAAAJ&hl=en
Motivation for joining: Biomedical imaging is a field that optimizes and facilitates tasks of the medical professionals. Being able to help doctors achieve more accurate and faster diagnosis and therefore be more efficient in their job is very motivating, since it shows how our team can implement computer science and engineering knowledge in interdisciplinary projects.
Motivation for joining: Biomedical imaging is a field that optimizes and facilitates tasks of the medical professionals. Being able to help doctors achieve more accurate and faster diagnosis and therefore be more efficient in their job is very motivating, since it shows how our team can implement computer science and engineering knowledge in interdisciplinary projects.
Merim Jusufbegović
About: Dr.sci. Merim Jusufbegović is a senior assistant in Radiological Technology at the Faculty of Health Studies and a Radiographer at the Clinical Center University of Sarajevo. With a PhD in Health Studies, his expertise lies in 3D printing for medical applications, including creating patient-specific anatomical models, medical phantoms, and educational tools. His work focuses on enhancing medical training, optimizing imaging protocols, and developing innovative solutions in biomedical engineering.
Merim Jusufbegović
About: Dr.sci. Merim Jusufbegović is a senior assistant in Radiological Technology at the Faculty of Health Studies and a Radiographer at the Clinical Center University of Sarajevo. With a PhD in Health Studies, his expertise lies in 3D printing for medical applications, including creating patient-specific anatomical models, medical phantoms, and educational tools. His work focuses on enhancing medical training, optimizing imaging protocols, and developing innovative solutions in biomedical engineering.
Motivation for joining: Biomedical Imaging has the potential to transform diagnostic accuracy, optimize imaging protocols, and improve patient outcomes. My interest lies in integrating AI with 3D printing to enhance medical image analysis, automate segmentation, and develop patient-specific solutions. By combining AI-driven insights with advanced fabrication techniques, I aim to contribute to precision medicine, making diagnostics more efficient and accessible.
Motivation for joining: Biomedical Imaging has the potential to transform diagnostic accuracy, optimize imaging protocols, and improve patient outcomes. My interest lies in integrating AI with 3D printing to enhance medical image analysis, automate segmentation, and develop patient-specific solutions. By combining AI-driven insights with advanced fabrication techniques, I aim to contribute to precision medicine, making diagnostics more efficient and accessible.
Nerma Kadrić
About: I am a Bachelor of Electrical Engineering with a strong passion for mathematics and computer science. Currently, I am a first-year Master’s student in Computer Science and Informatics at the Faculty of Electrical Engineering in Sarajevo. This semester, I am on an exchange program in France, as a Master's student in the Internet of Things program, at the University of Franche Comte. During my academic journey, I have completed an internship where I gained valuable experience as a full-stack developer. This experience helped me develop both practical and soft skills, enhancing my understanding of software development. My recent research focuses on AI, particularly biomedical image analysis, classification, and Generative Adversarial Networks (GANs). I am particularly passionate about the intersection of AI, embedded systems, and IoT, and how these technologies can be used to create innovative and impactful solutions.
Nerma Kadrić
About: I am a Bachelor of Electrical Engineering with a strong passion for mathematics and computer science. Currently, I am a first-year Master’s student in Computer Science and Informatics at the Faculty of Electrical Engineering in Sarajevo. This semester, I am on an exchange program in France, as a Master's student in the Internet of Things program, at the University of Franche Comte. During my academic journey, I have completed an internship where I gained valuable experience as a full-stack developer. This experience helped me develop both practical and soft skills, enhancing my understanding of software development. My recent research focuses on AI, particularly biomedical image analysis, classification, and Generative Adversarial Networks (GANs). I am particularly passionate about the intersection of AI, embedded systems, and IoT, and how these technologies can be used to create innovative and impactful solutions.
Motivation for joining: I am fascinated by the possibility of Artificial Intelligence to transform healthcare, especially in the area of the extraction of relevant information from images to obtain valuable insights which will aid doctors. Biomedical image analysis enables me to combine my passion for technology with my desire to make a positive impact on society.
Motivation for joining: I am fascinated by the possibility of Artificial Intelligence to transform healthcare, especially in the area of the extraction of relevant information from images to obtain valuable insights which will aid doctors. Biomedical image analysis enables me to combine my passion for technology with my desire to make a positive impact on society.
Medina Kapo
About: Medina Kapo earned both her Bachelor’s and Master’s degrees in Electrical Engineering, specializing in Computing and Informatics, at the Faculty of Electrical Engineering, University of Sarajevo. During her studies, she was a student demonstrator for the “Fundamentals of Database Systems” course. From October 2022 to July 2023, she served as the student representative for the second year of the Master’s program in Computing and Informatics. Additionally, in 2023, she was a mentor in artificial intelligence at the IT Girls Bootcamp – Smarter (IT) girls, smarter automation. Currently, she is an teaching and research assistant and PhD candidate at the same faculty. Her recent research primarily focuses on computer vision tasks, particularly semantic segmentation and super-resolution, as well as optimizing neural network inference processes using the OpenVINO toolkit. She has also worked on the Advertis project as technical support and is currently involved in a project utilizing natural language processing for digital content analysis. Her future PhD dissertation will be related to bioinformatics and cheminformatics, with more details to be revealed in the future.
Medina Kapo
About: Medina Kapo earned both her Bachelor’s and Master’s degrees in Electrical Engineering, specializing in Computing and Informatics, at the Faculty of Electrical Engineering, University of Sarajevo. During her studies, she was a student demonstrator for the “Fundamentals of Database Systems” course. From October 2022 to July 2023, she served as the student representative for the second year of the Master’s program in Computing and Informatics. Additionally, in 2023, she was a mentor in artificial intelligence at the IT Girls Bootcamp – Smarter (IT) girls, smarter automation. Currently, she is an teaching and research assistant and PhD candidate at the same faculty. Her recent research primarily focuses on computer vision tasks, particularly semantic segmentation and super-resolution, as well as optimizing neural network inference processes using the OpenVINO toolkit. She has also worked on the Advertis project as technical support and is currently involved in a project utilizing natural language processing for digital content analysis. Her future PhD dissertation will be related to bioinformatics and cheminformatics, with more details to be revealed in the future.
Motivation for joining: Strong passion for medicine, image processing, and artificial intelligence has naturally led me to join the Biomedical Imaging team, where these fields are seamlessly integrated. I strongly believe that AI model integration is becoming essential for achieving more accurate and precise diagnostics.
Motivation for joining: Strong passion for medicine, image processing, and artificial intelligence has naturally led me to join the Biomedical Imaging team, where these fields are seamlessly integrated. I strongly believe that AI model integration is becoming essential for achieving more accurate and precise diagnostics.
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