Konstantinos completed his Bachelor’s degree in Physics at National and Kapodistrian University of Athens in Greece, and is currently pursuing his Masters in Medical Imaging from Utrecht University. As part of his studies, he worked for his Major research project at UMC Utrecht on the use of Deep Learning for scatter corrections in PET imaging under the supervision of Woutjan Branderhorst and Hugo de Jong.
In July 2022, he joined the Computational Imaging Group for his Minor Research Project, under the supervision of Matteo Maspero. Within the project, we investigate the use of invertible recurrent inference machines (iRIMs) for Cone-Beam CT image reconstruction. The aim is to obtain a fast image reconstruction method that provides CT-grade, noiseless and artifact-free images from CBCT sinograms. This could potentially enable the use of CBCT over conventional CT for online treatment plan adaptations in radiotherapy.
Keywords: Deep Learning | Image reconstruction | Cone-beam CT