TY - JOUR
T1 - High-performance GPU-based rendering for real-time, rigid 2D/3D-image registration and motion prediction in radiation oncology
AU - Spoerk, Jakob
AU - Gendrin, Christelle
AU - Weber, Christoph
AU - Figl, Michael
AU - Pawiro, Supriyanto Ardjo
AU - Furtado, Hugo
AU - Fabri, Daniella
AU - Bloch, Christoph
AU - Bergmann, Helmar
AU - Gröller, Eduard
AU - Birkfellner, Wolfgang
N1 - Funding Information:
This work was supported by the Austrian Science Foundation FWF project L 503 and P 19931. S. A. Pawiro holds a scholarship for the Eurasisa-Pacific UNINET foundation. The spine dataset and ground truth for the 2D/3D registration used in this work was provided by the Image Sciences Institute, University Medical Center Utrecht, The Netherlands.
PY - 2012/2
Y1 - 2012/2
N2 - A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D Registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference x-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512 × 512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches - namely so-called wobbled splatting - to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT.
AB - A common problem in image-guided radiation therapy (IGRT) of lung cancer as well as other malignant diseases is the compensation of periodic and aperiodic motion during dose delivery. Modern systems for image-guided radiation oncology allow for the acquisition of cone-beam computed tomography data in the treatment room as well as the acquisition of planar radiographs during the treatment. A mid-term research goal is the compensation of tumor target volume motion by 2D/3D Registration. In 2D/3D registration, spatial information on organ location is derived by an iterative comparison of perspective volume renderings, so-called digitally rendered radiographs (DRR) from computed tomography volume data, and planar reference x-rays. Currently, this rendering process is very time consuming, and real-time registration, which should at least provide data on organ position in less than a second, has not come into existence. We present two GPU-based rendering algorithms which generate a DRR of 512 × 512 pixels size from a CT dataset of 53 MB size at a pace of almost 100 Hz. This rendering rate is feasible by applying a number of algorithmic simplifications which range from alternative volume-driven rendering approaches - namely so-called wobbled splatting - to sub-sampling of the DRR-image by means of specialized raycasting techniques. Furthermore, general purpose graphics processing unit (GPGPU) programming paradigms were consequently utilized. Rendering quality and performance as well as the influence on the quality and performance of the overall registration process were measured and analyzed in detail. The results show that both methods are competitive and pave the way for fast motion compensation by rigid and possibly even non-rigid 2D/3D registration and, beyond that, adaptive filtering of motion models in IGRT.
KW - 2D/3D-Registration
KW - DRR
KW - Real-time
KW - Sparse sampling
UR - http://www.scopus.com/inward/record.url?scp=84858160942&partnerID=8YFLogxK
U2 - 10.1016/j.zemedi.2011.06.002
DO - 10.1016/j.zemedi.2011.06.002
M3 - Article
C2 - 21782399
AN - SCOPUS:84858160942
SN - 0939-3889
VL - 22
SP - 13
EP - 20
JO - Zeitschrift fur Medizinische Physik
JF - Zeitschrift fur Medizinische Physik
IS - 1
ER -