@inproceedings{136ad91582624193b14544f18ca5a9f2,
title = "Comparison of optimization strategy and similarity metric in atlas-to-subject registration using statistical deformation model",
abstract = "A robust atlas-to-subject registration using a statistical deformation model (SDM) is presented. The SDM uses statistics of voxel-wise displacement learned from pre-computed deformation vectors of a training dataset. This allows an atlas instance to be directly translated into an intensity volume and compared with a patient's intensity volume. Rigid and nonrigid transformation parameters were simultaneously optimized via the Covariance Matrix Adaptation - Evolutionary Strategy (CMA-ES), with image similarity used as the objective function. The algorithm was tested on CT volumes of the pelvis from 55 female subjects. A performance comparison of the CMA-ES and Nelder-Mead downhill simplex optimization algorithms with the mutual information and normalized cross correlation similarity metrics was conducted. Simulation studies using synthetic subjects were performed, as well as leave-one-out cross validation studies. Both studies suggested that mutual information and CMA-ES achieved the best performance. The leave-one-out test demonstrated 4.13 mm error with respect to the true displacement field, and 26, 102 function evaluations in 180 seconds, on average.",
keywords = "Atlas-to-subject registration, Evolutionary optimization, Statistical deformation model",
author = "Y. Otake and Murphy, {R. J.} and Grupp, {R. B.} and Y. Sato and Taylor, {R. H.} and M. Armand",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling ; Conference date: 22-02-2015 Through 24-02-2015",
year = "2015",
doi = "10.1117/12.2081754",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Webster, {Robert J.} and Yaniv, {Ziv R.}",
booktitle = "Medical Imaging 2015",
}