Intensity-Based volumetric registration of contrast-enhanced MR breast images

Authors:
Yin Sun;Chye Hwang Yan;Sim-Heng Ong;Ek Tsoon Tan;Shih-Chang Wang
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore;Department of Electrical and Computer Engineering, National University of Singapore;Department of Electrical and Computer Engineering, National University of Singapore;Department of Electrical and Computer Engineering, National University of Singapore;Department of Diagnostic Radiology, National University of Singapore
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2006

Citing 6
Cited 0

Multi-modal Volume Registration Using Joint Intensity Distributions

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
The Correlation Ratio as a New Similarity Measure for Multimodal Image Registration

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Volume and Shape Preservation of Enhancing Lesions when Applying Non-rigid Registration to a Time Series of Contrast Enhancing MR Breast Images

MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees

IEEE Transactions on Information Technology in Biomedicine
Optimization of mutual information for multiresolution image registration

IEEE Transactions on Image Processing
Fast parametric elastic image registration

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a fast intensity-based registration algorithm for the analysis of contrast-enhanced breast MR images. Motion between pre-contrast and post-contrast images has been modeled by a combination of rigid transformation and free-form deformation. By modeling the conditional probability function to be Gaussian and considering the normalized mutual information (NMI) criterion, we create a pair of auxiliary images to speed up the registration process. The auxiliary images are registered to the actual images by optimizing the simple sum of squared difference (SSD) criterion. The overall registration is achieved by linearly combining the deformation observed in the auxiliary images. One well-known problem of non-rigid registration of contrast enhanced images is the contraction of enhanced lesion volume. We address this problem by rejecting the intensity outliers from registration. Results have shown that our method could achieve accurate registration of the data while successfully prevent the contraction of the contrast enhanced lesion volume.