The research group for medical image analysis combines competence in medicine, mathematics, engineering, artificial intelligence (AI), and data technology to develop new solutions for the health sector. We work on the analysis of medical images like MR, CT, ultrasound, or microscopy, among others, and develop methods which can support clinicians during diagnostics, treatment, and follow-up of patients.
The group has deep competence in machine learning and AI for computer vision, image-guided treatment, multimodal data analysis, and visualisation. We also develop decision support tools that combine imaging data with other types of health records in addition to methods for image-guided surgery, and robotics,
Our research addresses major societal challenges such as cancer and cardiovascular diseases. At the same time, we work closely with hospitals, hospital trust, technology companies, and the public sector to ensure that our solutions are useful for the clinical practice.
We research in close collaboration with clinical environments and users to develop technology with solves concrete challenges in healthcare. Through the whole research process we collaborate with doctors, radiologists, nurses, hospitals, and industrial partners to ensure that our methods are relevant, robust, and useful.
The research group develops algorithms and analysis methods supported with large medical datasets and advanced AI models. We work both on basic method development, and on testing and validation in clinical settings.
We combine experimental research with software development, prototyping, and user involvement. This gives us a foundation to build bridges between research and implementation, and to contribute to the fact that new technology can be used in healthcare services.
What sets us apart is the combination of strong technological expertise, a good understanding of user needs, and close integration with clinical environments. We have extensive experience in developing solutions that work in complex healthcare ecosystems, where requirements for quality, privacy, and user-friendliness are crucial.
The research group has extensive experience in translating research into practical tools and solutions. We work across disciplines and connect expertise in image analysis, AI, mathematics, engineering, visualization, and health informatics.
Through our position as an independent research institute, we can bring together actors from academia, healthcare, and business around common challenges and contribute to innovation with great societal benefit.
The research group participates in several international research projects and collaborates with leading universities, hospitals, and research institutions in Europe, and the rest of the world. We are active in EU-funded projects and contribute to the development of international research networks within medical image analysis and AI in health.
Our researchers regularly publish in leading international journals and conferences. And several of the solutions and methods we develop are used in international research and innovation projects.
Through international collaboration, we gain access to large and diverse datasets, new methodological approaches, and strong academic environments that strengthen the quality and relevance of our research.
Do you want to use AI or other image analysis in diagnostics, treatment, research, or medical technology development? Do you need help analysing large amounts of medical images, or developing decision support based on health data?
We can assist with:
We collaborate with both healthcare actors, the public sector, start-ups and established industry.
We are always open to new collaborations opportunities. Contact us to learn more about our research and how can we work together to develop the future of health technology. Together we can bring up new solutions in medical image analysis, AI, and digital health, either through research projects, innovation collaborations, strategic consultations or exchange of expertise.
The main goal of the project is to improve the clinical understanding of relationships between clinical/radiological characteristics, disease courses, and treatment responses in patients with central nervous system tumors. The project focuses on...
We will enable medical imaging in remote areas by using artificial intelligence to guide ultrasound in real-time. Thereby improving remote health care services and its environmental and economic sustainability.
The HoloSurge project will provide surgeons with a visualization and navigation tool that can improve clinical decision-making and reduce the risk of surgical complications in cancer surgery.
Our primary objective, and vision, is to enable early AKI diagnosis through the determination of renal blood flow autoregulation.
The primary goal of this project is to test if ultrasound scanning of the thyroid gland is feasible using a robotic arm, without any radiologist present.
