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Review of Techniques for Registration of Diffusion Tensor Imaging

  • Chapter
Tensors in Image Processing and Computer Vision

Part of the book series: Advances in Pattern Recognition ((ACVPR))

Abstract

Image registration is a common image processing task, and therefore, many algorithms have been proposed and described to carry it out for different image modalities. However, the application of these algorithms to diffusion tensor imaging is not straightforward due to the special features of this kind of data, where a tensor is defined at each voxel. The information provided by the diffusion tensor is related to the anatomical structures in tissues, and this relation should be preserved, even though the image has been transformed by a registration procedure. On the other hand, the registration problem can be viewed as an optimization problem, where a similarity measure has to be maximized. The appropriate definition of this similarity measure is indeed an important issue for the registration of diffusion tensor images. In this paper, we compile the different approaches for the registration of diffusion tensor images that have been published. Special attention is paid to the aforementioned topics: how to preserve the coherence between the tensor and the underlying tissue structure, and how to measure the similarity between two diffusion tensors. Methods to evaluate results are also reviewed, since a reliable validation leads to more conclusive results, specially in the comparison of different techniques. Most challenging issues for diffusion tensor images registration are underlined, and open research lines about this topic are pointed out.

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Authors and Affiliations

  1. Laboratory of Image Processing, University of Valladolid, Spain

    Emma Muñoz-Moreno, Rubén Cárdenes-Almeida & Marcos Martin-Fernandez

Authors
  1. Emma Muñoz-Moreno
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  2. Rubén Cárdenes-Almeida
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  3. Marcos Martin-Fernandez
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Correspondence to Emma Muñoz-Moreno .

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Editors and Affiliations

  1. Escuela Técnica Superior de Ingenieros de Telecomunicacíon, Universidad de Valladolid, Campus Miguel Delibes, 47011 Valladolid, Spain

    Santiago Aja-Fernández  & Rodrigo de Luis García  & 

  2. Dept. Computing, HongKong Polytechnic University, Hong Kong

    Dacheng Tao

  3. University of London Birkbeck College School of Computer Science & Information Systems, Malet Street, London, WC1E 7HX, UK

    Xuelong Li

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Muñoz-Moreno, E., Cárdenes-Almeida, R., Martin-Fernandez, M. (2009). Review of Techniques for Registration of Diffusion Tensor Imaging. In: Aja-Fernández, S., de Luis García, R., Tao, D., Li, X. (eds) Tensors in Image Processing and Computer Vision. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-299-3_13

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  • DOI: https://doi.org/10.1007/978-1-84882-299-3_13

  • Publisher Name: Springer, London

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