MR and CT data with multiobserver delineations of organs in the pelvic area-Part of the Gold Atlas project

Research output: Contribution to journalArticle

Abstract

Purpose: We describe a public dataset with MR and CT images of patients performed in the same position with both multiobserver and expert consensus delineations of relevant organs in the male pelvic region. The purpose was to provide means for training and validation of segmentation algorithms and methods to convert MR to CT like data, i.e., so called synthetic CT (sCT). Acquisition and validation methods: T1- and T2-weighted MR images as well as CT data were collected for 19 patients at three different departments. Five experts delineated nine organs for each patient based on the T2-weighted MR images. An automatic method was used to fuse the delineations. Starting from each fused delineation, a consensus delineation was agreed upon by the five experts for each organ and patient. Segmentation overlap between user delineations with respect to the consensus delineations was measured to describe the spread of the collected data. Finally, an open-source software was used to create deformation vector fields describing the relation between MR and CT images to further increase the usability of the dataset. Data format and usage notes: The dataset has been made publically available to be used for academic purposes, and can be accessed from https://zenodo.org/record/583096. Potential applications: The dataset provides a useful source for training and validation of segmentation algorithms as well as methods to convert MR to CT-like data (sCT). To give some examples: The T2-weighted MR images with their consensus delineations can directly be used as a template in an existing atlas-based segmentation engine; the expert delineations are useful to validate the performance of a segmentation algorithm as they provide a way to measure variability among users which can be compared with the result of an automatic segmentation; and the pairwise deformably registered MR and CT images can be a source for an atlas-based sCT algorithm or for validation of sCT algorithm.

Details

Authors
  • Tufve Nyholm
  • Stina Svensson
  • Sebastian Andersson
  • Joakim Jonsson
  • Maja Sohlin
  • Christian Gustafsson
  • Elisabeth Kjellén
  • Karin Söderström
  • Per Albertsson
  • Lennart Blomqvist
  • Björn Zackrisson
  • Lars E. Olsson
  • Adalsteinn Gunnlaugsson
Organisations
External organisations
  • Umeå University
  • RaySearch Laboratories AB
  • Sahlgrenska University Hospital
  • Skåne University Hospital
  • Karolinska Institutet
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Hematology
  • Cancer and Oncology

Keywords

  • CT, MRI, Open dataset, Organs at risk, Radiotherapy
Original languageEnglish
Pages (from-to)1295-1300
JournalMedical Physics
Volume45
Issue number3
Publication statusPublished - 2018 Mar
Publication categoryResearch
Peer-reviewedYes