Registration of bone structures in 3D ultrasound and CT data: comparison of different optimization strategies
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Registration of bone structures in 3D ultrasound and CT data : comparison of different optimization strategies. / Winter, Susanne; Brendel, Bernhard; Igel, Christian.
In: International Congress Series, Vol. 1281, 2005, p. 242-247.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Registration of bone structures in 3D ultrasound and CT data
AU - Winter, Susanne
AU - Brendel, Bernhard
AU - Igel, Christian
N1 - Conference code: 19
PY - 2005
Y1 - 2005
N2 - We developed a fast and robust algorithm to register intraoperative three-dimensional ultrasound data of the spine with preoperative CT data. We compared different gradient-based and evolutionary optimization strategies for solving the registration problem. The iRprop, a fast gradient-based optimization algorithm, quickly and reliably led to higher registration rates than the two established methods BFGS and conjugate gradient descent (CG). The Covariance Matrix Adaptation evolution strategy (CMA) yielded the best results concerning registration rate and accuracy but at the cost of a slightly higher number of evaluations of the optimization criterion compared to CG and iRprop. The CMA was able to register patient data starting from a realistic misalignment in 98% of the trials in about 15 s per registration.
AB - We developed a fast and robust algorithm to register intraoperative three-dimensional ultrasound data of the spine with preoperative CT data. We compared different gradient-based and evolutionary optimization strategies for solving the registration problem. The iRprop, a fast gradient-based optimization algorithm, quickly and reliably led to higher registration rates than the two established methods BFGS and conjugate gradient descent (CG). The Covariance Matrix Adaptation evolution strategy (CMA) yielded the best results concerning registration rate and accuracy but at the cost of a slightly higher number of evaluations of the optimization criterion compared to CG and iRprop. The CMA was able to register patient data starting from a realistic misalignment in 98% of the trials in about 15 s per registration.
KW - Evolutionary optimization
KW - Image registration
KW - Spine
KW - Ultrasound
U2 - 10.1016/j.ics.2005.03.351
DO - 10.1016/j.ics.2005.03.351
M3 - Conference article
AN - SCOPUS:33646458732
VL - 1281
SP - 242
EP - 247
JO - International Congress Series
JF - International Congress Series
SN - 0531-5131
Y2 - 22 June 2005 through 25 June 2005
ER -
ID: 168565998