1H imaging

Magnetic resonance imaging (MRI) has transformed biomedical research and clinical practice, offering unparalleled views of tissue structure and function at the metabolic and physiological levels. Its non-invasive nature, coupled with continuous advancements in methods and technologies, drives the development of innovative imaging strategies. A key focus of this evolution is increasing sensitivity, pushing the field towards ever-higher magnetic field strengths.

With the recent clinical approval of 7 Tesla MRI for imaging the head and extremities, the availability of these so-called ultra-high field (UHF) systems is increasing worldwide. 7 Tesla MRI has already demonstrated substantial clinical benefits, particularly in the diagnosis of neurodegenerative diseases. The advantages of 7 Tesla MRI stem from its significantly enhanced signal-to-noise ratio (SNR) compared to lower field strengths. This translates to improved contrast-to-noise ratio, enabling higher spatial and/or temporal resolutions, as well as improved accuracy in quantitative MRI.

Our project group is dedicated to maximizing the potential of 7 Tesla MRI for human proton (1H) imaging, aiming to achieve unprecedented levels of detail and sensitivity. We pursue this goal through the active development of novel hardware components and innovative RF management strategies. Furthermore, we optimize existing imaging methods – focusing on image contrast, artifact reduction, and SNR efficiency – to address the unique technical challenges inherent in operating at such high field strengths.

Research Topics

  • Development of novel receiver arrays for 7 Tesla body imaging

  • Advanced RF management strategies

  • Novel imaging sequences and optimization of acquisition parameters for UHF applications

  • Development of advanced quantitative flow imaging techniques

  • Translation of 7 Tesla MRI techniques into clinical applications

Contact

1 Employees

  • Dr. Simon Schmidt

    Project group leader

    Contact form: Message to Dr. Simon Schmidt

    Form data is loaded ...