Imke has a background in biomedical engineering and uses an interdisciplinary approach to study the risk factors contributing to an increase in fracture risk of bone. Musculoskeletal tissues such as bone, muscle and tendon are hierarchical structures, where numerous interfaces within and between the tissues play an important role in maintaining their biomechanical performance. Combining various imaging and analytical tools from the whole body level to the tissue level, i.e., from the macro- to the nanoscale, can help to gain a better understanding of the interfaces contributing to the integrity of the musculoskeletal system. Imke holds a research specialist position in the ICCIR and focuses on high resolution imaging and multi-scale material characterization. Her special interest is on establishing small-sized laboratory fish models to study tissues at the interface during musculoskeletal development, aging and in case of diseases in vivo.

The research focus of the Institute of Medical Technology and Intelligent Systems at Hamburg University of Technology includes robotics, image processing, and image guidance as well as the development and adaptation of machine learning approaches and optimization methods for clinical applications. We are particularly interested in detecting and compensating motion and deformation of tissue structures, e.g., using spatio-temporal deep learnings and fast volumetric imaging like OCT and ultrasound. We collaborate with a range of clinical partners, including from cardiology, oncology, neurology, surgery, and radiation therapy with applications ranging from radiation therapy treatment plan optimization to robotic needle placements.

With a background in medical engineering, Max’s main research focus is in the field of elastography and real-time data processing. By using fast imaging modalities such as optical coherence tomography (OCT) and ultrasound imaging we can track excited shear waves inside soft tissue. Mapping the elasticity in a minimally invasive fashion and generating elasticity maps in real-time is a main focus. We acquire 3D and 4D image data and study multi-dimensional neural networks for real-time prediction of elasticity. Next to superficial imaging devices we also focus on minimal invasive needle probes with integrated elasticity sensing. We study if a surgeon can feel tissue interfaces during needle insertions while a robot applies haptic feedback. Essentially, the surgeon will navigate by sensing the tissue interfaces.

The Institute for Biomedical Imaging (IBI) is a joint institute of the University Medical Center Hamburg-Eppendorf and the Hamburg University of Technology and focuses on image reconstruction within several tomographic imaging techniques. In particular the new method magnetic particle imaging is researched and new image reconstruction and artifact reduction algorithms are developed for the method. In addition to image reconstruction, the institute investigates new imaging sequences and new scanner hardware. In the field of magnetic resonance imaging and computed tomography, the institute develops algorithms for accelerated and dose reduced measurement protocols and for multi-contrast imaging.

Having a background in physics and biomedical imaging, Mirco’s main research focus are algorithmic techniques for image reconstruction and artifact reduction in different imaging modalities such as magnetic particle imaging and magnetic resonance imaging. A common aspect of modern image reconstruction techniques is the targeted use of prior knowledge in order to reduce measurement time, increase image quality or mitigate imaging artifacts. This can either be achieved using classical optimization techniques or using modern data-driven approaches. To facilitate research at the interface of different imaging techniques, Mirco puts a focus on the development of reconstruction tools within a common framework that is both flexible and easily extendable.