Comparative Visual Analysis of Pelvic Organ Segmentations

Oliver Reiter, Marcel Breeuwer, Meister Eduard Gröller, Renata Raidou
Comparative Visual Analysis of Pelvic Organ Segmentations
Computer Graphics Forum, 2018. [Honorable Mention ] [paper] [Video]

Information

Abstract

In prostate cancer treatment, automatic segmentations of the pelvic organs are often used as input to radiotherapy planning systems. However, natural anatomical variability of the involved organs is a common reason, for which segmentation algorithms fail, introducing errors in the radiotherapy treatment procedure, as well. Understanding how the shape and size of these organs affect the accuracy of segmentation is of major importance for developers of segmentation algorithms. However, current means of exploration and analysis provide limited insight. In this work, we discuss the design and implementation of a web-based framework, which enables easy exploration and detailed analysis of shape variability, and allows the intended users - i.e., segmentation experts - to generate hypotheses in relation to the performance of the involved algorithms. Our proposed approach was tested with segmentation meshes from a small cohort of 17 patients. Each mesh consists of four pelvic organs and two organ interfaces, which are labeled and have per-triangle correspondences. A usage scenario and an initial informal evaluation with a segmentation expert demonstrate that our framework allows the developers of the algorithms to quickly identify inaccurately segmented organs and to deliberate about the relation of variability to anatomical features and segmentation quality.

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BibTeX

@article{EuroVis2018-ShortPapers-Reiter,
  title =      "Comparative Visual Analysis of Pelvic Organ Segmentations",
  author =     "Oliver Reiter and Marcel Breeuwer and Meister Eduard
               Gr\"{o}ller and Renata Raidou",
  year =       "2018",
  abstract =   "In prostate cancer treatment, automatic segmentations of the
               pelvic organs are often used as input to radiotherapy
               planning systems. However, natural anatomical variability of
               the involved organs is a common reason, for which
               segmentation algorithms fail, introducing errors in the
               radiotherapy treatment procedure, as well. Understanding how
               the shape and size of these organs affect the accuracy of
               segmentation is of major importance for developers of
               segmentation algorithms. However, current means of
               exploration and analysis provide limited insight. In this
               work, we discuss the design and implementation of a
               web-based framework, which enables easy exploration and
               detailed analysis of shape variability, and allows the
               intended users - i.e., segmentation experts - to generate
               hypotheses in relation to the performance of the involved
               algorithms. Our proposed approach was tested with
               segmentation meshes from a small cohort of 17 patients. Each
               mesh consists of four pelvic organs and two organ
               interfaces, which are labeled and have per-triangle
               correspondences. A usage scenario and an initial informal
               evaluation with a segmentation expert demonstrate that our
               framework allows the developers of the algorithms to quickly
               identify inaccurately segmented organs and to deliberate
               about the relation of variability to anatomical features and
               segmentation quality.",
  doi =        "10.2312/eurovisshort.20181075",
  journal =    "Computer Graphics Forum",
  crossref =   "EuroVis2018-ShortPapers-proc",
  pages =      "037-041",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2018/EuroVis2018-ShortPapers-Reiter/",
}