An approach to generate synthetic 4DCT datasets to benchmark Mid-Position implementations.

Firass Ghareeb¹, Djamal Boukerroui², Joep Stroom³, Edward Jackson⁴, Mariana Pereira¹, Mark Gooding², Carlo Greco¹

¹Champalimaud Foundation, Department of Radiation Oncology, Lisbon, Portugal.

²Mirada Medical Ltd., Oxford, United Kingdom.

³Champalimaud Foundation, Department of Radiation Oncology, Lisbon, Portugal. Electronic address: joep.stroom@fundacaochampalimaud.pt.

⁴Netherlands Cancer Institute, Amsterdam, Netherlands.

PubMed DOI

Abstract

PURPOSE: The Mid-Position image is constructed from 4DCT data using Deformable Image Registration and can be used as planning CT with reduced PTV volumes. 4DCT datasets currently-available for testing do not provide the corresponding Mid-P images of the datasets. This work describes an approach to generate human-like synthetic 4DCT datasets with the associated Mid-P images that can be used as refe…

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