TY - CONF T1 - Spectral clustering to model deformations for fast multimodal prostate registration T2 - International Conference on Pattern Recognition (ICPR) Y1 - 2012 A1 - Jhimli Mitra A1 - Zoltan Kato A1 - Soumya Ghose A1 - Desire Sidibe A1 - Robert Martí A1 - Xavier Lladó A1 - Oliver Arnau A1 - Joan C Vilanova A1 - Fabrice Meriaudeau ED - Jan-Olof Eklundh ED - Yuichi Ohta ED - Steven Tanimoto AB -

This paper proposes a method to learn deformation parameters off-line for fast multimodal registration of ultrasound and magnetic resonance prostate images during ultrasound guided needle biopsy. The registration method involves spectral clustering of the deformation parameters obtained from a spline-based nonlinear diffeomorphism between training magnetic resonance and ultrasound prostate images. The deformation models built from the principal eigen-modes of the clusters are then applied on a test magnetic resonance image to register with the test ultrasound prostate image. The deformation model with the least registration error is finally chosen as the optimal model for deformable registration. The rationale behind modeling deformations is to achieve fast multimodal registration of prostate images while maintaining registration accuracies which is otherwise computationally expensive. The method is validated for 25 patients each with a pair of corresponding magnetic resonance and ultrasound images in a leave-one-out validation framework. The average registration accuracies i.e. Dice similarity coefficient of 0.927 ± 0.025, 95% Hausdorff distance of 5.14 ± 3.67 mm and target registration error of 2.44 ± 1.17 mm are obtained by our method with a speed-up in computation time by 98% when compared to Mitra et al. [7].

 

JF - International Conference on Pattern Recognition (ICPR) PB - IEEE CY - Tsukuba, Japan SN - 978-1-4673-2216-4 UR - http://hal.archives-ouvertes.fr/docs/00/71/09/43/PDF/ICPR_Jhimli.pdf ER -