AI4Science Seminar: Unsupervised Domain Adaptation for Optoacoustic Imaging

Talk at the SDSC AI4Science Seminar (EPFL, Lausanne): Unsupervised Domain Adaptation for Optoacoustic Imaging: Leveraging Unpaired Data for Improved Results.

Optoacoustic imaging involves the reconstruction of tissue images from acoustic signals generated by a light source. In this talk, I described challenges in optoacoustic imaging, supervised translation with limited-quality paired datasets, and improvements achieved with unsupervised image-to-image translation using unpaired datasets (e.g., CycleGAN). Joint work with the Multiscale Functional and Molecular Imaging Lab at ETH Zurich.