The quantification of absolute molecular concentrations can be considered the holy grail of multispectral photoacoustic imaging (PAI). I am interested in applying machine learning methods to investigate this challenge, as solving it would enable accurate spectral unmixing of local blood oxygenation and open numerous exciting clinical applications. I build tissue-mimicking materials and digital representations of these (“digital twins”) and image them with PAI – I can use these to (1) calibrate the numerical forward models needed to simulate PAI and (2) to simulate realistic data distributions that allow the training of deep learning algorithms on simulated data.
Brief CV
- BSc Medical Informatics, Heilbronn University of Applied Sciences, Germany (2011-2014)
- MSc Medical Informatics, Heidelberg University, Germany (2014 – 2016)
- PhD Medical Informatics, German Cancer Research Center, Heidelberg, Germany (2016 – 2020)
- Postdoc Photoacoustic Imaging, German Cancer Research Center, Heidelberg, Germany (2020)
Publication Highlights
Best conference attended
SPIE Photonics West, Photons plus Ultrasound, February 2019