Medical Imaging focusses on using imaging and image analysis to achieve more reliable (personalized) diagnosis and prognosis and to provide guidance resulting in more accurate and effective interventions with faster recovery and fewer side effects.
It is a rapidly growing field, because of the fast increase in the size, complexity and sheer number of images acquired in clinical practice. The aim is to support clinicians in their decisions, in order to provide safer and better care.
Image analysis can play a role in all stages of care: from screening and diagnosis to treatment and finally to monitoring of therapy. Examples of applications that we work on are analysis of brain structure, early detection of retinal abnormalities and improved prognosis for breast cancer patients.
Challenges & breakthroughs
- Quantitatively analyze (vast amounts of) data
- Guide interventions by imaging and image analysis (real-time, movement)
- Advance predictive modeling from populations to individual patients
- Improve efficiency and effectiveness
- Reduce burden of care on patient and society
- From automated to autonomous
- From limited applicability to routine clinical care (accuracy, reliability, speed)
The level of complexity will increase in time: starting with the analysis of images, proceeding towards implementing this analysis in decision support in the clinical workflow and improving patient care.
- Philips Healthcare / Philips research
- Pie Medical Imaging / 3mensio
- UMCU / MUMC / LUMC / Erasmus MC / AMC / MMC / Catharina Ziekenhuis / Jeroen Bosch Ziekenhuis
- Kempenhaeghe Epilepsy Institute
- TU Delft
- Harvard Medical School
- University of Bonn
- He University / Eye Hospital, Shenyang, China
- Shengjing Hospital, Shenyang, China
- Northeastern University, Shenyang, China
- Brainnetome China
For questions or more information about this research, please contact theme leader prof.dr. Josien Pluim.