Medical imaging encompasses a versatile toolkit of methods to generate anatomical images of a single organ or even the entire patient for diagnostic and therapeutic purposes. Radiation-based imaging technologies are of inestimable importance and hence performed in daily clinical practice.
Electromagnetic radiation may, however, cause undesirable side effects. Consequently, methods allowing for dose reduction are expected to prospectively come into focus. This may specifically hold for patients, who need to be scanned periodically for therapy and/or health progress monitoring.
Instead of performing an entire scan per session, prior knowledge derived from preexisting multimodal image data sourcing, anatomical atlases, as well as mathematical models may be integrated — the latter reducing radiation dose and scan duration thus finally saving health expenditures.
In order to do so, available images and data need to be updated based on newly acquired subsampled data.
The application of prior knowledge may furthermore advance minimally invasive interventions by means of intraoperative image acquisition. Within this context, consecutive scans usually show a high degree of similarity while differing only in probe position and respiratory organ motion. Lower radiation loads vs. significant increases in image frame rate may result when spotting those similiarities based on formerly acquired image information.
The integration of prior knowledge therefore holds a great potential for improving contemporary interventional procedures — especially in the field of interventional magnetic resonance imaging (IMRI).
Graduates in medical imaging science, medical engineering or engineering, computer, and natural science will have the opportunity to work with high-tech diagnostic devices such as x-ray examination and computed tomography (CT), state-of-the-art single-photon emission computed tomography (SPECT) and positron emission tomography (PET) within a structured 4-year/48-month PhD track.
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