TY - GEN
T1 - Real-time intensity based 2D/3D registration for tumor motion tracking during radiotherapy
AU - Furtado, Hugo
AU - Gendrin, Christelle
AU - Bloch, Christoph
AU - Spoerk, Jakob
AU - Pawiro, Suprianto A.
AU - Weber, Christoph
AU - Figl, Michael
AU - Bergmann, Helmar
AU - Stock, Markus
AU - Georg, Dietmar
AU - Birkfellner, Wolfgang
PY - 2012
Y1 - 2012
N2 - Organ motion during radiotherapy is one of the causes of uncertainty in dose delivery creating the need to enlarge the planned target volume (PTV) to guarantee full tumor irradiation. In this work, we investigate the feasibility of using real-time 2D/3D registration for tumor motion tracking during radiotherapy based on purely intensity based image processing, thus avoiding markers or fiducials. X-rays are acquired during treatment at a rate of 5.4 Hz. We iteratively compare each x-ray with a set of digitally reconstructed radiographs (DRR) generated from the planning volume dataset, finding the optimal match between the xray and one of the DRRs. The DRRs are generated using a ray-casting algorithm, implemented using general purpose computation on graphics hardware (GPGPU) for best performance. Validation is conducted offline using a phantom and five clinical patient data sets. The phantom motion is measured with an RMS error of 2.1 mm and mean registration time is 220 ms. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is seen. Mean registration time is always under 105 ms which is well suited for our purposes. These results demonstrate that real-time organ motion monitoring using image based markerless registration is feasible.
AB - Organ motion during radiotherapy is one of the causes of uncertainty in dose delivery creating the need to enlarge the planned target volume (PTV) to guarantee full tumor irradiation. In this work, we investigate the feasibility of using real-time 2D/3D registration for tumor motion tracking during radiotherapy based on purely intensity based image processing, thus avoiding markers or fiducials. X-rays are acquired during treatment at a rate of 5.4 Hz. We iteratively compare each x-ray with a set of digitally reconstructed radiographs (DRR) generated from the planning volume dataset, finding the optimal match between the xray and one of the DRRs. The DRRs are generated using a ray-casting algorithm, implemented using general purpose computation on graphics hardware (GPGPU) for best performance. Validation is conducted offline using a phantom and five clinical patient data sets. The phantom motion is measured with an RMS error of 2.1 mm and mean registration time is 220 ms. For the patient data sets, a sinusoidal movement that clearly correlates to the breathing cycle is seen. Mean registration time is always under 105 ms which is well suited for our purposes. These results demonstrate that real-time organ motion monitoring using image based markerless registration is feasible.
UR - http://www.scopus.com/inward/record.url?scp=84884480717&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-28502-8_37
DO - 10.1007/978-3-642-28502-8_37
M3 - Contribution to conference proceeding
AN - SCOPUS:84884480717
SN - 9783642285011
T3 - Informatik aktuell
SP - 207
EP - 212
BT - Bildverarbeitung fur die Medizin 2012
PB - Kluwer Academic Publishers
T2 - Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2012 - Workshop on Image Processing for Medicine: Algorithms - Systems - Applications, BVM 2012
Y2 - 18 March 2012 through 20 March 2012
ER -