Abstract
In this paper, we propose an improved B-spline registration algorithm for feature fusion of images from different neuroimaging techniques. The current B-spline registration method generally consists of several steps: initial curve estimation, similarity estimation between the warped image and fixed image, gradient computation, optimization and curve re-estimation. We improved the accuracy and efficiency of gradient computation by introducing a map-reduce framework which partitions the volume into multiple subregions and each subregion can be processed independently and efficiently. Experimental results show that our method achieves higher accuracy than the traditional registration algorithm and computational burden is released for large scale neuroimages.
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© 2015 Springer International Publishing Switzerland
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Jiang, P., Shackleford, J.A. (2015). B-Spline Registration of Neuroimaging Modalites with Map-Reduce Framework. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds) Brain Informatics and Health. BIH 2015. Lecture Notes in Computer Science(), vol 9250. Springer, Cham. https://doi.org/10.1007/978-3-319-23344-4_28
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DOI: https://doi.org/10.1007/978-3-319-23344-4_28
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