De-enhancing the Dynamic Contrast-Enhanced Breast MRI for Robust Registration
Dynamic enhancement causes serious problems for registration of contrast enhanced breast MRI, due to variable uptakes of agent on different tissues or even same tissues in the breast. We present an iterative optimization algorithm to de-enhance the dynamic contrast-enhanced breast MRI and then register them for avoiding the effects of enhancement on image registration. In particular, the spatially varying enhancements are modeled by a Markov Random Field, and estimated by a locally smooth function with boundaries using a graph cut algorithm. The de-enhanced images are then registered by conventional B-spline based registration algorithm. These two steps benefit from each other and are repeated until the results converge. Experimental results show that our two-step registration algorithm performs much better than conventional mutual information based registration algorithm. Also, the effects of tumor shrinking in the conventional registration algorithms can be effectively avoided by our registration algorithm.
KeywordsNormalize Mutual Information Registration Algorithm Nonrigid Registration Iterative Optimization Algorithm Dynamic Magnetic Resonance Breast Image
- 3.Tanner, C., et al.: Volume and shape preservation of enhancing lesions when applying non-rigid registration to a time series of contrast enhancing MR breast images. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 327–337. Springer, Heidelberg (2000)Google Scholar
- 5.Papademetris, X.: Integrated intensity and point-feature nonrigid registration. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, Springer, Heidelberg (2004)Google Scholar
- 9.Chen, X., et al.: Simultanous segmentation and registration of contrast-enhanced breast MRI. In: Christensen, G.E., Sonka, M. (eds.) IPMI 2005. LNCS, vol. 3565, Springer, Heidelberg (2005)Google Scholar
- 10.Boykov, Y., et al.: Fast approximate energy minimization via graph cuts. IEEE Trans. PAMI 23, 1222–1239 (2001)Google Scholar
- 12.Chen, X., et al.: Simultanous segmentation and registration for medical image. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, Springer, Heidelberg (2004)Google Scholar