Abstract: Deep Learning Based CT-CBCT Image Registration for Adaptive Radio Therapy

Sven Kuckertz*, Nils Papenberg, Jonas Honegger, Tomasz Morgas, Benjamin Haas, Stefan Heldmann

*Corresponding author for this work


Deformable image registration (DIR) is an important tool in radio therapy where it is used in order to align a baseline CT and daily low-dose cone beam CT (CBCT) scans. DIR allows the propagation of irradiation plans, Hounsfield units and contours of anatomical structures, respectively, which enables tracking of applied doses over time and generation of daily synthetic CT images. Furthermore, DIR allows to overcome segmentation of structures in CBCT images at each fraction.

Original languageEnglish
Title of host publicationBildverarbeitung für die Medizin 2020
EditorsThomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm
Number of pages1
PublisherSpringer Vieweg, Wiesbaden
Publication date12.02.2020
ISBN (Print)978-3-658-29266-9
ISBN (Electronic)978-3-658-29267-6
Publication statusPublished - 12.02.2020
EventBildverarbeitung für die Medizin 2020 - International workshop on Algorithmen - Systeme - Anwendungen
- Berlin, Germany
Duration: 15.03.202017.03.2020
Conference number: 237969


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