Spatial warping of DWI data using sparse representation

Pew Thian Yap, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Registration of DWI data, unlike scalar image data, is complicated by the need of reorientation algorithms for keeping the orientation architecture of each voxel aligned with the rest of the image. This paper presents an algorithm for effective and efficient warping and reconstruction of diffusion-weighted imaging (DWI) signals for the purpose of spatial transformation. The key idea is to decompose the DWI signal profile, a function defined on a unit sphere, into a series of weighted fiber basis functions (FBFs), reorient these FBFs independently based on the local affine transformation, and then recompose the reoriented FBFs to obtain the final transformed DWI signal profile. We enforce a sparsity constraint on the weights of the FBFs during the decomposition to reflect the fact that the DWI signal profile typically gains its information from a limited number of fiber populations. A non-negative constraint is further imposed so that noise-induced negative lobes in the profile can be avoided. The proposed framework also explicitly models the isotropic component of the diffusion signals to avoid undesirable reorientation artifacts in signal reconstruction. In contrast to existing methods, the current algorithm is executed directly in the DWI signal space, thus allowing any diffusion models to be fitted to the data after transformation.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI2012 - 15th International Conference, Proceedings
EditorsGeorg Langs, Antonio Criminisi, Georg Langs, Bjoern H. Menze, Nicholas Ayache, Hervé Delingette, Le Lu, Bjoern H. Menze, Zhuowen Tu, Albert Montillo, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Pages331-338
Number of pages8
ISBN (Print)9783642334177
DOIs
Publication statusPublished - 2012
Event15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France
Duration: 2012 Oct 52012 Oct 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period12/10/512/10/5

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yap, P. T., & Shen, D. (2012). Spatial warping of DWI data using sparse representation. In G. Langs, A. Criminisi, G. Langs, B. H. Menze, N. Ayache, H. Delingette, L. Lu, B. H. Menze, Z. Tu, A. Montillo, P. Golland, & K. Mori (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI2012 - 15th International Conference, Proceedings (pp. 331-338). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7511 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-642-33418-4_41