Abstract
The estimation and subsequent use of tissue T1(x) parameters at each image location x can potentially lead to a more reliable classification of breast tissues. T1 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 T1 estimation. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Lo, J. L. C., Brady, M., & Moore, N. (2006). Simultaneous multiple image registration method for T1 estimation in breast MRI images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4190 LNCS-I, pp. 865–872). Springer Verlag. https://doi.org/10.1007/11866565_106
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