Yuanjie Zheng, Jingyi Yu, Chandra Kambhamettu, Dinggang Shen
to appear the 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007)
| 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.
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De-enhancing
the Dynamic Contrast-Enhanced Breast MRI for Robust Registration Yuanjie Zheng, Jingyi Yu, Chandra Kambhamettu, Dinggang Shen to appear the 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007) |