TY - GEN
T1 - Optimising the verification of patient positioning in proton beam therapy
AU - Ransome, Trevor M.
AU - Rubin, David M.
AU - Marwala, Tshilidzi
AU - De Kock, Evan A.
PY - 2005
Y1 - 2005
N2 - A new patient positioning system incorporating a robotic arm is currently being designed for proton beam therapy. This requires aligning a treatment image with a pre-defined reference image. This is achieved by the alignment of the radiation and reference field boundaries, followed by registering the patient's anatomy relative to the boundary. This paper compares and tests methods for both field boundary and anatomy alignment. For field boundary alignment it is proposed to use a powerful object detection algorithm known as the generalised Hough transform (GHT). It was found that the GHT algorithm, followed by an optimisation routine, worked successfully and overcame problems in existing solutions. For anatomical-body alignment, a number of intensity-based similarity measures and optimisation routines are tested. It was found that the genetic algorithm, minimising the correlation coefficient similarity measure worked the best.
AB - A new patient positioning system incorporating a robotic arm is currently being designed for proton beam therapy. This requires aligning a treatment image with a pre-defined reference image. This is achieved by the alignment of the radiation and reference field boundaries, followed by registering the patient's anatomy relative to the boundary. This paper compares and tests methods for both field boundary and anatomy alignment. For field boundary alignment it is proposed to use a powerful object detection algorithm known as the generalised Hough transform (GHT). It was found that the GHT algorithm, followed by an optimisation routine, worked successfully and overcame problems in existing solutions. For anatomical-body alignment, a number of intensity-based similarity measures and optimisation routines are tested. It was found that the genetic algorithm, minimising the correlation coefficient similarity measure worked the best.
UR - http://www.scopus.com/inward/record.url?scp=33749056810&partnerID=8YFLogxK
U2 - 10.1109/ICCCYB.2005.1511587
DO - 10.1109/ICCCYB.2005.1511587
M3 - Conference contribution
AN - SCOPUS:33749056810
SN - 0780391225
SN - 9780780391222
T3 - ICCC 2005 - IEEE 3rd International Conference on Computational Cybernetics - Proceedings
SP - 279
EP - 284
BT - ICCC 2005 - IEEE 3rd International Conference on Computational Cybernetics - Proceedings
T2 - ICCC 2005 - IEEE 3rd International Conference on Computational Cybernetics
Y2 - 13 April 2005 through 16 April 2005
ER -