TY - GEN

T1 - Efficient nonrigid registration using ranked order statistics

AU - Tennakoon, Ruwan B.

AU - Bab-Hadiashar, Alireza

AU - de Bruijne, Marleen

AU - Cao, Zhenwei

N1 - Conference code: 10

PY - 2013

Y1 - 2013

N2 - Non-rigid image registration techniques are widely used in medical imaging applications. Due to high computational complexities of these techniques, finding appropriate registration method to both reduce the computation burden and increase the registration accuracy has become an intense area of research. In this paper we propose a fast and accurate non-rigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of real lung CT images, with expert annotated landmarks, show that the new method is both faster and more accurate than the state of the art techniques, particularly for registration of images with large deformations.

AB - Non-rigid image registration techniques are widely used in medical imaging applications. Due to high computational complexities of these techniques, finding appropriate registration method to both reduce the computation burden and increase the registration accuracy has become an intense area of research. In this paper we propose a fast and accurate non-rigid registration method for intra-modality volumetric images. Our approach exploits the information provided by an order statistics based segmentation method, to find the important regions for registration and use an appropriate sampling scheme to target those areas and reduce the registration computation time. A unique advantage of the proposed method is its ability to identify the point of diminishing returns and stop the registration process. Our experiments on registration of real lung CT images, with expert annotated landmarks, show that the new method is both faster and more accurate than the state of the art techniques, particularly for registration of images with large deformations.

U2 - 10.1109/ISBI.2013.6556520

DO - 10.1109/ISBI.2013.6556520

M3 - Article in proceedings

AN - SCOPUS:84881644287

SN - 978-1-4673-6456-0

T3 - International Symposium on Biomedical Imaging. Proceedings

SP - 496

EP - 499

BT - 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI)

PB - IEEE

Y2 - 7 April 2013 through 11 April 2013

ER -