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

Nyholm, Tufve; Svensson, Stina; Andersson, Sebastian; Jonsson, Joakim; Sohlin, Maja; Gustafsson, Christian LU ; Kjellén, Elisabeth LU ; Söderström, Karin; Albertsson, Per and Blomqvist, Lennart, et al. (2018) In Medical Physics
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... (More)

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.

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Contribution to journal
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in press
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keywords
CT, MRI, Open dataset, Organs at risk, Radiotherapy
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Medical Physics
publisher
American Association of Physicists in Medicine
external identifiers
  • scopus:85040965918
ISSN
0094-2405
DOI
10.1002/mp.12748
language
English
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yes
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9b8ae6b9-513d-46a8-a846-09aacbc2d39c
date added to LUP
2018-02-26 17:40:59
date last changed
2018-05-29 11:38:46
@article{9b8ae6b9-513d-46a8-a846-09aacbc2d39c,
  abstract     = {<p>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.</p>},
  author       = {Nyholm, Tufve and Svensson, Stina and Andersson, Sebastian and Jonsson, Joakim and Sohlin, Maja and Gustafsson, Christian and Kjellén, Elisabeth and Söderström, Karin and Albertsson, Per and Blomqvist, Lennart and Zackrisson, Björn and Olsson, Lars E. and Gunnlaugsson, Adalsteinn},
  issn         = {0094-2405},
  keyword      = {CT,MRI,Open dataset,Organs at risk,Radiotherapy},
  language     = {eng},
  publisher    = {American Association of Physicists in Medicine},
  series       = {Medical Physics},
  title        = {MR and CT data with multiobserver delineations of organs in the pelvic area-Part of the Gold Atlas project},
  url          = {http://dx.doi.org/10.1002/mp.12748},
  year         = {2018},
}