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De-enhancing the Dynamic Contrast-Enhanced Breast MRI for Robust Registration

  • Yuanjie Zheng
  • Jingyi Yu
  • Chandra Kambhamettu
  • Sarah Englander
  • Mitchell D. Schnall
  • Dinggang Shen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4791)

Abstract

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.

Keywords

Normalize Mutual Information Registration Algorithm Nonrigid Registration Iterative Optimization Algorithm Dynamic Magnetic Resonance Breast Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yuanjie Zheng
    • 1
    • 2
  • Jingyi Yu
    • 2
  • Chandra Kambhamettu
    • 2
  • Sarah Englander
    • 1
  • Mitchell D. Schnall
    • 1
  • Dinggang Shen
    • 1
  1. 1.Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104USA
  2. 2.Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716USA

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