Low Rank and Sparse Matrix Decomposition as Stroke Segmentation Prior: Useful or Not? A Random Forest-Based Evaluation Study

  • René Werner
  • Daniel Schetelig
  • Thilo Sothmann
  • Eike Mücke
  • Matthias Wilms
  • Bastian Cheng
  • Nils D. Forkert
Conference paper
Part of the Informatik aktuell book series (INFORMAT)

Abstract

Manual ischemic stroke lesion segmentation in MR image data is a time-consuming task subject to inter-rater variability. Reliable automated lesion segmentation is of high interest for clinical trials and research in ischemic stroke. However, recent segmentation challenges (e.g. ISLES 2015) illustrate that current state-of-the-art approaches still lack accuracy and ischemic stroke segmentation remains a complicated problem. Within this context, low rank-&-sparse matrix decomposition (also known as robust PCA, RPCA) and RPCA-based non-linear subject-toatlas registration could provide valuable segmentation prior information. The aim of this study is to evaluate the suitability of RPCA and RPCAbased registration for ischemic stroke segmentation in follow-up FLAIR MR data sets. Building on a top-ranked segmentation approach of ISLES 2015, the performance of RPCA sparse component image information as random forest (RF) feature is evaluated. A comprehensive feature-byfeature comparison of the segmentation performance with and without RPCA sparse component information as RF feature illustrate the potential of low rank-&-sparse decomposition to improve stroke segmentation.

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Copyright information

© Springer-Verlag GmbH Deutschland 2017

Authors and Affiliations

  • René Werner
    • 1
  • Daniel Schetelig
    • 1
  • Thilo Sothmann
    • 1
  • Eike Mücke
    • 1
  • Matthias Wilms
    • 2
  • Bastian Cheng
    • 3
  • Nils D. Forkert
    • 4
  1. 1.University Medical Center Hamburg-EppendorfDepartment of Computational NeuroscienceHamburgDeutschland
  2. 2.University of LübeckInstitute of Medical InformaticsHamburgDeutschland
  3. 3.Department of NeurologyUniversity Medical Center Hamburg-EppendorfHamburgDeutschland
  4. 4.Department of Radiology & Hotchkiss Brain InstituteUniversity of CalgaryCalgaryCanada

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