Abraham George Smith

PhD student Computer Science, Rigshospitalet, Copenhagen ags@di.ku.dk

DK: Den grundlæggende tanke bag Abrahams projekt er at kombinere registerdata med automatiseret billedanalyse ved brug af kunstig intelligens – deep learning

Læs mere om Abrahams projekt.

UK: Abraham's project involves deep learning-based medical image segmentation for routine radiotherapy planning and to establish new dose-response relationships from historical data. The project has a focus on interactive methods for continual learning. Structures investigated include blood vessels in the lungs, organs at risk and cardiac sub-structures.

Read more about Abraham's project.

Arbejdsgrupper Publikationer
  • Abraham George Smith, Jens Petersen, Cynthia Terrones-Campos , Anne Kiil Berthelsen, Nora Jarrett Forbes, Sune Darkner, Lena Specht, Ivan Richter Vogelius RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy Med Phys. 2022 Jan;49(1):461-473 2022
  • Isak Wahlstedt, Nicolaus Andratschke, Claus P Behrens, Stefanie Ehrbar, Hubert S Gabryś, Helena Garcia Schüler, Matthias Guckenberger, Abraham George Smith, Stephanie Tanadini-Lang, José D Tascón-Vidarte , Ivan R Vogelius, Janita E van Timmeren 2 Gating has a negligible impact on dose delivered in MRI-guided online adaptive radiotherapy of prostate cancer Radiother Oncol. 2022 May;170:205-212 2022
  • Isak Wahlstedt, Abraham George Smith, Claus Erik Andersen, Claus Preibisch Behrens, Susanne Nørring Bekke, Kristian Boye, Mette van Overeem Felter, Mirjana Josipovic, Jens Petersen, Signe Lenora Risumlund, José David Tascón-Vidarte, Janita Elizabeth van Timmeren, Ivan Richter Vogelius Interfractional dose accumulation for MR-guided liver SBRT: Variation among algorithms is highly patient- and fraction-dependent Radiotherapy and Oncology 2022