CBCT Image Correction
At the Department of Radiation Oncology of the University Hospital of the LMU Munich, extensive expertise in CBCT image correction is available. This has been continuously developed since the first activities initiated in 2013 by the Department of Medical Physics of the Faculty of Physics of the LMU Munich in Garching (Prof. Katia Parodi) within the BMBF-funded SPARTA project. The joint effort has seen the development of CBCT correction methods allowing accurate photon and proton dose calculations for various treatment sites. The initial approach during SPARTA was to use deformable image registration (DIR) to map CT image intensities to the anatomy shown in CBCT scans of head and neck cancer patients, a method referred to as virtual CT. Subsequent collaborative work led to the development of projection-based correction using the virtual CT as a scatter-free prior. Recently, the two groups have focused on using deep learning to accelerate scatter correction, using the popular U-net and cycle-consistent GAN designs in collaboration with the Aarhus University Hospital and the University Medical Center Utrecht, respectively. The latter collaboration was supported by the German Cancer Aid in the scope of a Mildred-Scheel Postdoctoral Fellowship.
- Kurz C, Maspero M, Savenije MHF, Landry G, Kamp F, Pinto M, Li M, Parodi K, Belka C, Van den Berg CAT. CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation. Physics in Medicine and Biology. 2019 Nov;64(22): 225004
- Landry G, Hansen D, Kamp F, Li M, Hoyle B, Weller J, Parodi K, Belka C, Kurz C. Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations. Physics in Medicine & Biology. 2019 Jan 24;64(3):035011.
- Hansen DC, Landry G, Kamp F, Li M, Belka C, Parodi K, Kurz C. ScatterNet: A convolutional neural network for cone‐beam CT intensity correction. Medical physics. 2018 Nov;45(11):4916-26.
- Zöllner C, Rit S, Kurz C, Vilches-Freixas G, Kamp F, Dedes G, Belka C, Parodi K, Landry G. Decomposing a prior-CT-based cone-beam CT projection correction algorithm into scatter and beam hardening components. Physics and Imaging in Radiation Oncology. 2017 Jul 1;3:49-52.
- Kurz C., Kamp F., Park Y.K., Zöllner C., Rit S., Hansen D., Podesta M., Sharp G.C., Li M., Reiner M., Hofmaier J., Neppl S., Thieke C., Nijhuis R., U. Ganswindt, C. Belka, B.A. Winey, K. Parodi, G. Landry 2016. Investigating deformable image registration and scatter correction for CBCT‐based dose calculation in adaptive IMPT. Medical physics, 43(10), pp.5635-5646.
- Kurz C, Nijhuis R, Reiner M, Ganswindt U, Thieke C, Belka C, Parodi K, Landry G. Feasibility of automated proton therapy plan adaptation for head and neck tumors using cone beam CT images. Radiation Oncology. 2016 Dec 1;11(1):64.
- Kurz C., Dedes G., Resch A., Reiner M., Ganswindt U., Nijhuis R., Thieke C., Belka C., Parodi K. and Landry G., 2015. Comparing cone-beam CT intensity correction methods for dose recalculation in adaptive intensity-modulated photon and proton therapy for head and neck cancer. Acta oncologica, 54(9), pp.1651-1657.
- Landry G., Nijhuis R., Dedes G., Handrack J., Thieke C., Janssens G., Orban de Xivry J., Reiner M., Kamp F., Wilkens J.J., Paganelli C., Riboldi M., Baroni G., Ganswindt U., Belka C., and Parodi K, 2015. Investigating CT to CBCT image registration for head and neck proton therapy as a tool for daily dose recalculation. Medical Physics, 42(3), pp.1354-1366.
- Landry G., Dedes G., Zöllner C., Handrack J., Janssens G., de Xivry J.O., Reiner M., Paganelli C., Riboldi M., Kamp F., Söhn M., Wilkens J.J., Baroni G., Belka C., and Parodi K., 2014. Phantom based evaluation of CT to CBCT image registration for proton therapy dose recalculation. Physics in Medicine & Biology, 60(2), p.595.