Accurate Interactive Visualization of Large Deformations and Variability in Biomedical Image Ensembles

Max Hermann, Anja C. Schunke, Thomas Schultz, and Reinhard Klein
In: IEEE Trans. on Visualization and Computer Graphics (2016), 22:1(708-717)
 

Abstract

Large image deformations pose a challenging problem for the visualization and statistical analysis of 3D image ensembles which have a multitude of applications in biology and medicine. Simple linear interpolation in the tangent space of the ensemble introduces artifactual anatomical structures that hamper the application of targeted visual shape analysis techniques. In this work we make use of the theory of stationary velocity fields to facilitate interactive non-linear image interpolation and plausible extrapolation for high quality rendering of large deformations and devise an efficient image warping method on the GPU. This does not only improve quality of existing visualization techniques, but opens up a field of novel interactive methods for shape ensemble analysis. Taking advantage of the efficient non-linear 3D image warping, we showcase four visualizations: 1) browsing on-the-fly computed group mean shapes to learn about shape differences between specific classes, 2) interactive reformation to investigate complex morphologies in a single view, 3) likelihood volumes to gain a concise overview of variability and 4) streamline visualization to show variation in detail, specifically uncovering its component tangential to a reference surface. Evaluation on a real world dataset shows that the presented method outperforms the state-of-the-art in terms of visual quality while retaining interactive frame rates. A case study with a domain expert was performed in which the novel analysis and visualization methods are applied on standard model structures, namely skull and mandible of different rodents, to investigate and compare influence of phylogeny, diet and geography on shape. The visualizations enable for instance to distinguish (population-)normal and pathological morphology, assist in uncovering correlation to extrinsic factors and potentially support assessment of model quality.

Keywords: image warping, interactive visual analysis, stationary velocity fields, Statistical deformation model

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Bibtex

@ARTICLE{hermann2015-vis,
    author = {Hermann, Max and Schunke, Anja C. and Schultz, Thomas and Klein, Reinhard},
     pages = {708--717},
     title = {Accurate Interactive Visualization of Large Deformations and Variability in Biomedical Image
              Ensembles},
   journal = {IEEE Trans. on Visualization and Computer Graphics},
    volume = {22},
    number = {1},
      year = {2016},
  keywords = {image warping, interactive visual analysis, stationary velocity fields, Statistical deformation
              model},
  abstract = {Large image deformations pose a challenging problem for the visualization and statistical analysis
              of 3D image ensembles which have a multitude of applications in biology and medicine. Simple linear
              interpolation in the tangent space of the ensemble introduces artifactual anatomical structures that
              hamper the application of targeted visual shape analysis techniques. In this work we make use of the
              theory of stationary velocity fields to facilitate interactive non-linear image interpolation and
              plausible extrapolation for high quality rendering of large deformations and devise an efficient
              image warping method on the GPU. This does not only improve quality of existing visualization
              techniques, but opens up a field of novel interactive methods for shape ensemble analysis. Taking
              advantage of the efficient non-linear 3D image warping, we showcase four visualizations: 1) browsing
              on-the-fly computed group mean shapes to learn about shape differences between specific classes, 2)
              interactive reformation to investigate complex morphologies in a single view, 3) likelihood volumes
              to gain a concise overview of variability and 4) streamline visualization to show variation in
              detail, specifically uncovering its component tangential to a reference surface. Evaluation on a
              real world dataset shows that the presented method outperforms the state-of-the-art in terms of
              visual quality while retaining interactive frame rates. A case study with a domain expert was
              performed in which the novel analysis and visualization methods are applied on standard model
              structures, namely skull and mandible of different rodents, to investigate and compare influence of
              phylogeny, diet and geography on shape. The visualizations enable for instance to distinguish
              (population-)normal and pathological morphology, assist in uncovering correlation to extrinsic
              factors and potentially support assessment of model quality.}
}