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[LAK+98]  Visualizing Diffusion Tensor Images of the Mouse Spinal Cord

Laidlaw:1998:VDT (In proceedings)
Author(s)Laidlaw D., Ahrens E., Kremers D., Avalos M., Jacobs R. and Readhead C.
Title« Visualizing Diffusion Tensor Images of the Mouse Spinal Cord »
InProceedings of the 1998 IEEE Conference on Visualization (VIS'98)
Page(s)127--134
Year1998
PublisherIEEE Computer Society
AddressLos Alamitos, CA
URLhttp://dx.doi.org/10.1109/VISUAL.1998.745294

Abstract
Within biological systems water molecules undergo continuous stochastic Brownian motion. The rate of this diffusion can give clues to the structure of underlying tissues. In some tissues the rate is anisotropic — faster in some directions than others. Diffusion-rate images are second-order tensor fields and can be calculated from diffusion-weighted magnetic resonance images. A 2D diffusion tensor image (DTI) and an associated anatomical scalar field, created during the tensor calculation, de.ne seven values at each spatial location. Visually representing these images is a challenge because they contain so many inter-related components. We present two new methods for visually representing DTIs. The first method displays an array of ellipsoids where the shape of each ellipsoid represents one tensor value. The novel aspect of this representation is that the ellipsoids are all normalized to approximately the same size so that they can be displayed simultaneously in context. The second method uses concepts from oil painting to represent the seven-valued data with multiple layers of varying brush strokes. Both methods successfully display most or all of the information in DTIs and provide exploratory methods for understanding them. The ellipsoid method has a simpler interpretation and explanation than the painting-motivated method; the painting-motivated method displays more of the information and is easier to read quantitatively. We demonstrate the methods on images of the mouse spinal cord. The visualizations show significant differences between spinal cords from mice suffering from Experimental Allergic Encephalomyelitis (EAE) and spinal cords from wild-type mice. The differences are consistent with differences shown histologically and suggest that our new non-invasive imaging methodology and visualization of the results could have early diagnostic value for neurodegenerative diseases.

BibTeX code
@inproceedings{Laidlaw:1998:VDT,
  opteditor = {},
  optpostscript = {},
  optorganization = {},
  author = {David H. Laidlaw and Eric T. Ahrens and David Kremers and Matthew J.
            Avalos and Russell E. Jacobs and Carol Readhead},
  optkey = {},
  optannote = {},
  optseries = {},
  url = {http://dx.doi.org/10.1109/VISUAL.1998.745294},
  address = IEEEAdr,
  localfile = {papers/Laidlaw.1998.VDT.pdf},
  optisbn = {},
  publisher = IEEEPub,
  optkeywords = {},
  doi = {http://doi.ieeecomputersociety.org/10.1109/VISUAL.1998.745294},
  optmonth = {},
  citeseer = {http://citeseer.ist.psu.edu/laidlaw98visualizing.html},
  optcrossref = {},
  optwww = {},
  booktitle = {Proceedings of the 1998 IEEE Conference on Visualization
               (VIS'98)},
  optvolume = {},
  optnumber = {},
  abstract = {Within biological systems water molecules undergo continuous
              stochastic Brownian motion. The rate of this diffusion can give
              clues to the structure of underlying tissues. In some tissues the
              rate is anisotropic — faster in some directions than others.
              Diffusion-rate images are second-order tensor fields and can be
              calculated from diffusion-weighted magnetic resonance images. A 2D
              diffusion tensor image (DTI) and an associated anatomical scalar
              field, created during the tensor calculation, de.ne seven values
              at each spatial location. Visually representing these images is a
              challenge because they contain so many inter-related components.
              We present two new methods for visually representing DTIs. The
              first method displays an array of ellipsoids where the shape of
              each ellipsoid represents one tensor value. The novel aspect of
              this representation is that the ellipsoids are all normalized to
              approximately the same size so that they can be displayed
              simultaneously in context. The second method uses concepts from
              oil painting to represent the seven-valued data with multiple
              layers of varying brush strokes. Both methods successfully display
              most or all of the information in DTIs and provide exploratory
              methods for understanding them. The ellipsoid method has a simpler
              interpretation and explanation than the painting-motivated method;
              the painting-motivated method displays more of the information and
              is easier to read quantitatively. We demonstrate the methods on
              images of the mouse spinal cord. The visualizations show
              significant differences between spinal cords from mice suffering
              from Experimental Allergic Encephalomyelitis (EAE) and spinal
              cords from wild-type mice. The differences are consistent with
              differences shown histologically and suggest that our new
              non-invasive imaging methodology and visualization of the results
              could have early diagnostic value for neurodegenerative diseases.
              },
  title = {{V}isualizing {D}iffusion {T}ensor {I}mages of the {M}ouse {S}pinal
           {C}ord},
  year = {1998},
  pages = {127--134},
}

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