Modeling 4D Changes in Pathological Anatomy Using Domain Adaptation: Analysis of TBI Imaging Using a Tumor Database

  • Bo Wang
  • Marcel Prastawa
  • Avishek Saha
  • Suyash P. Awate
  • Andrei Irimia
  • Micah C. Chambers
  • Paul M. Vespa
  • John D. Van Horn
  • Valerio Pascucci
  • Guido Gerig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8159)

Abstract

Analysis of 4D medical images presenting pathology (i.e., lesions) is significantly challenging due to the presence of complex changes over time. Image analysis methods for 4D images with lesions need to account for changes in brain structures due to deformation, as well as the formation and deletion of new structures (e.g., edema, bleeding) due to the physiological processes associated with damage, intervention, and recovery. We propose a novel framework that models 4D changes in pathological anatomy across time, and provides explicit mapping from a healthy template to subjects with pathology. Moreover, our framework uses transfer learning to leverage rich information from a known source domain, where we have a collection of completely segmented images, to yield effective appearance models for the input target domain. The automatic 4D segmentation method uses a novel domain adaptation technique for generative kernel density models to transfer information between different domains, resulting in a fully automatic method that requires no user interaction. We demonstrate the effectiveness of our novel approach with the analysis of 4D images of traumatic brain injury (TBI), using a synthetic tumor database as the source domain.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Bo Wang
    • 1
    • 2
  • Marcel Prastawa
    • 1
    • 2
  • Avishek Saha
    • 1
    • 2
  • Suyash P. Awate
    • 1
    • 2
  • Andrei Irimia
    • 3
  • Micah C. Chambers
    • 3
  • Paul M. Vespa
    • 4
  • John D. Van Horn
    • 3
  • Valerio Pascucci
    • 1
    • 2
  • Guido Gerig
    • 1
    • 2
  1. 1.Scientific Computing and Imaging InstituteUniversity of UtahUSA
  2. 2.School of ComputingUniversity of UtahUSA
  3. 3.Institute for Neuroimaging and InformaticsUniversity of Southern CaliforniaUSA
  4. 4.Brain Injury Research CenterUniversity of California at Los AngelesUSA

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