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Simultaneous Multiple Image Registration Method for T1 Estimation in Breast MRI Images

  • Jonathan Lok-Chuen Lo
  • Michael Brady
  • Niall Moore
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

The estimation and subsequent use of tissue T 1(x) parameters at each image location x can potentially lead to a more reliable classification of breast tissues. T 1 values can be estimated using multiple (typically 3) MRI images of different flip angles. However, breathing and other slight movements can render the highly non-linear estimation procedure error-prone. In this paper, a simultaneous multiple image registration method is proposed to solve this problem. The registration method is built upon the idea of conserving inverse consistency and transitivity among the multiple image transformations. The algorithm is applied to both simulated data and real breast MRI images. The performance is compared with existing pairwise image registration method. The results clearly indicate that the simultaneous multiple image registration algorithm leads to much more accurate T 1 estimation.

Keywords

Registration Method Diethylene Triamine Pentaacetic Acid White Pixel Image Registration Method 1Estimation Error 
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 2006

Authors and Affiliations

  • Jonathan Lok-Chuen Lo
    • 1
  • Michael Brady
    • 1
  • Niall Moore
    • 2
  1. 1.Wolfson Medical Vision LaboratoryUniversity of OxfordOxfordUK
  2. 2.MRI unitJohn Radcliffe HospitalOxfordUK

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