@string{mia="Medical Image Analysis"}
@ARTICLE{Mitra-etal2012,
  author = {Jhimli Mitra and Zoltan Kato and Robert Marti and Arnau Oliver and
	Xavier Llado and Desire Sidibe and Soumya Ghose and Joan C. Vilanova
	and Josep Comet and Fabrice Meriaudeau},
  title = {A spline-based non-linear diffeomorphism for multimodal prostate
	registration},
  journal = mia,
  year = {2012},
  volume = {16},
  pages = {1259--1279},
  number = {6},
  month = aug,
  abstract = {This paper presents a novel method for non-rigid registration of transrectal
	ultrasound and magnetic resonance prostate images based on a non-linear
	regularized framework of point correspondences obtained from a statistical
	measure of shape-contexts. The segmented prostate shapes are represented
	by shape-contexts and the Bhattacharyya distance between the shape
	representations is used to find the point correspondences between
	the 2D fixed and moving images. The registration method involves
	parametric estimation of the non-linear diffeomorphism between the
	multimodal images and has its basis in solving a set of non-linear
	equations of thin-plate splines. The solution is obtained as the
	least-squares solution of an over-determined system of non-linear
	equations constructed by integrating a set of non-linear functions
	over the fixed and moving images. However, this may not result in
	clinically acceptable transformations of the anatomical targets.
	Therefore, the regularized bending energy of the thin-plate splines
	along with the localization error of established correspondences
	should be included in the system of equations. The registration accuracies
	of the proposed method are evaluated in 20 pairs of prostate mid-gland
	ultrasound and magnetic resonance images. The results obtained in
	terms of Dice similarity coefficient show an average of 0.980 ±
	0.004, average 95\% Hausdorff distance of 1.63 ± 0.48 mm and mean
	target registration and target localization errors of 1.60 ± 1.17
	mm and 0.15 ± 0.12 mm respectively.}
}