Abstract
Automatic registration of brain MR images is still a challenging problem. We have chosen an approach based on landmarks matching. However, manual landmarking of the images is cumbersome. Existing algorithms for automatic identification of pre-defined set of landmarks usually require manually landmarked training bases. We propose the registration algorithm that involves automatic detection of landmarks with the use of only one manually landmarked template image. Landmarks are detected using Canny edge detector and point descriptors. Evaluation of four types of descriptors showed that SURF provides the best trade-off between speed and accuracy. Thin plate spline transformation is used for landmark-based registration. The proposed algorithm was compared with the best existing registration algorithm without the use of local features. Our algorithm showed significant speed-up and better accuracy in matching of anatomical structures surrounded by the landmarks. All the experiments were performed on the IBSR database.
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Acknowledgments
The authors would like to thank Alexey V. Petraikin, M.D. from Pirogov Russian National Research Medical University (RNRMU) for valuable discussion.
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Senyukova, O.V., Zobnin, D.S. (2015). Fast Brain MRI Registration with Automatic Landmark Detection Using a Single Template Image. In: Gall, J., Gehler, P., Leibe, B. (eds) Pattern Recognition. DAGM 2015. Lecture Notes in Computer Science(), vol 9358. Springer, Cham. https://doi.org/10.1007/978-3-319-24947-6_32
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