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Data for publication: Autoadaptive motion modelling for MR-based respiratory motion estimation

Baumgartner, Christian F.; Kolbitsch, Christoph; McClelland, Jamie R.; Rueckert, Daniel; King, Andrew P.


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{
  "description": "<p>This repository contains four&nbsp;T1-weighted&nbsp;2D MR slice datasets&nbsp;from multiple slice positions covering the entire thorax during free breathing and breath holds.&nbsp;&nbsp;The data was used to evaluate our novel autoadaptive respiratory motion model which we proposed in [1]. In particular, the datasets contain the following:</p>\n\n<ol>\n\t<li>Acquisition of all sagittal slice positions covering the thorax&nbsp;and one coronal slice position acquired during a breath hold.</li>\n\t<li>Results of registration between adjacent sagittal slice positions [control point displacements (cpp) and displacement fields (dfs)]</li>\n\t<li>40 dynamic acquisitions of each slice position also present in the breath-hold acquired during free breathing.&nbsp;</li>\n\t<li>Results of registration of the dynamic acquisitions to the respective&nbsp;breath-holds slices (cpp&#39;s and dfs&#39;s).&nbsp;</li>\n</ol>\n\n<p>The data is divided into 4 zip files, each containing the data of one volunteer. The folder structure for each is as follows:</p>\n\n<blockquote>\n<p>|-- bhs (breath hold data)<br />\n| &nbsp; |-- images (images)<br />\n| &nbsp; | &nbsp; |-- cor<br />\n| &nbsp; | &nbsp; `-- sag<br />\n| &nbsp; `-- mfs_slpos2slpos (registration results)<br />\n| &nbsp; &nbsp; &nbsp; `-- sag<br />\n`-- dyn (dynamic free-breathing data)<br />\n&nbsp; &nbsp; |-- images (images)<br />\n&nbsp; &nbsp; | &nbsp; |-- cor<br />\n&nbsp; &nbsp; | &nbsp; `-- sag<br />\n&nbsp; &nbsp; `-- mfs_tpos2tpos (registration results)<br />\n&nbsp; &nbsp; &nbsp; &nbsp; |-- cor<br />\n&nbsp; &nbsp; &nbsp; &nbsp; `-- sag</p>\n</blockquote>\n\n<p>Please, see our publication [1] for details on the acquisition sequence and registration&nbsp;used.&nbsp;</p>\n\n<p>--</p>\n\n<p>[1]: CF Baumgartner, C Kolbitsch, JR McClelland, D Rueckert, AP King, <em>Autoadaptive motion modelling for MR-based respiratory motion estimation</em>, Medical Image Analysis (2016),&nbsp;http://dx.doi.org/10.1016/j.media.2016.06.005</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Division of Imaging Sciences and Biomedical Engineering, King\u2019s College London, London, UK", 
      "@type": "Person", 
      "name": "Baumgartner, Christian F."
    }, 
    {
      "affiliation": "Division of Imaging Sciences and Biomedical Engineering, King\u2019s College London, London, UK", 
      "@type": "Person", 
      "name": "Kolbitsch, Christoph"
    }, 
    {
      "affiliation": "Centre for Medical Image Computing, University College London, London, UK", 
      "@type": "Person", 
      "name": "McClelland, Jamie R."
    }, 
    {
      "affiliation": "Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK", 
      "@type": "Person", 
      "name": "Rueckert, Daniel"
    }, 
    {
      "affiliation": "Division of Imaging Sciences and Biomedical Engineering, King\u2019s College London, London, UK", 
      "@type": "Person", 
      "name": "King, Andrew P."
    }
  ], 
  "url": "https://zenodo.org/record/55345", 
  "datePublished": "2016-06-10", 
  "keywords": [
    "MRI data, 2D, slice data, motion modelling, manifold alignment"
  ], 
  "@context": "https://schema.org/", 
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  ], 
  "identifier": "https://doi.org/10.5281/zenodo.55345", 
  "@id": "https://doi.org/10.5281/zenodo.55345", 
  "@type": "Dataset", 
  "name": "Data for publication: Autoadaptive motion modelling for MR-based respiratory motion estimation"
}
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