Summarizing and visualizing uncertainty in non-rigid registration

Authors:
Petter Risholm;Steve Pieper;Eigil Samset;William M. Wells, III
Affiliations:
Harvard Medical School, Brigham & Women's Hospital and Center of Mathematics for Applications, University of Oslo, NO;Harvard Medical School, Brigham & Women's Hospital;Center of Mathematics for Applications, University of Oslo, NO;Harvard Medical School, Brigham & Women's Hospital
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Year:
2010

Citing 4
Cited 8

MCMC curve sampling for image segmentation

MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Bootstrap resampling for image registration uncertainty estimation without ground truth

IEEE Transactions on Image Processing
Bayesian estimation of deformation and elastic parameters in non-rigid registration

WBIR'10 Proceedings of the 4th international conference on Biomedical image registration
Using registration uncertainty visualization in a user study of a simple surgical task

MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II

Probabilistic elastography: estimating lung elasticity

IPMI'11 Proceedings of the 22nd international conference on Information processing in medical imaging
Estimation of delivered dose in radiotherapy: the influence of registration uncertainty

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Longitudinal brain MRI analysis with uncertain registration

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Improving registration using multi-channel diffeomorphic demons combined with certainty maps

MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
A multi-image graph cut approach for cardiac image segmentation and uncertainty estimation

STACOM'11 Proceedings of the Second international conference on Statistical Atlases and Computational Models of the Heart: imaging and modelling challenges
Bayesian characterization of uncertainty in multi-modal image registration

WBIR'12 Proceedings of the 5th international conference on Biomedical Image Registration
Spatial confidence regions for quantifying and visualizing registration uncertainty

WBIR'12 Proceedings of the 5th international conference on Biomedical Image Registration
Bayesian estimation of regularization and atlas building in diffeomorphic image registration

IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging

Quantified Score

Hi-index	0.01

Visualization

Abstract

Registration uncertainty may be important information to convey to a surgeon when surgical decisions are taken based on registered image data. However, conventional non-rigid registration methods only provide the most likely deformation. In this paper we show how to determine the registration uncertainty, as well as the most likely deformation, by using an elastic Bayesian registration framework that generates a dense posterior distribution on deformations. We model both the likelihood and the elastic prior on deformations with Boltzmann distributions and characterize the posterior with a Markov Chain Monte Carlo algorithm. We introduce methods that summarize the high-dimensional uncertainty information and show how these summaries can be visualized in a meaningful way. Based on a clinical neurosurgical dataset, we demonstrate the importance that uncertainty information could have on neurosurgical decision making.