Data for publication: Autoadaptive motion modelling for MR-based respiratory motion estimation
<p>This repository contains four T1-weighted 2D MR slice datasets from multiple slice positions covering the entire thorax during free breathing and breath holds. 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> <ol> <li>Acquisition of all sagittal slice positions covering the thorax and one coronal slice position acquired during a breath hold.</li> <li>Results of registration between adjacent sagittal slice positions [control point displacements (cpp) and displacement fields (dfs)]</li> <li>40 dynamic acquisitions of each slice position also present in the breath-hold acquired during free breathing. </li> <li>Results of registration of the dynamic acquisitions to the respective breath-holds slices (cpp's and dfs's). </li> </ol> <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> <blockquote> <p>|-- bhs (breath hold data)<br /> | |-- images (images)<br /> | | |-- cor<br /> | | `-- sag<br /> | `-- mfs_slpos2slpos (registration results)<br /> | `-- sag<br /> `-- dyn (dynamic free-breathing data)<br /> |-- images (images)<br /> | |-- cor<br /> | `-- sag<br /> `-- mfs_tpos2tpos (registration results)<br /> |-- cor<br /> `-- sag</p> </blockquote> <p>Please, see our publication [1] for details on the acquisition sequence and registration used. </p> <p>--</p> <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), http://dx.doi.org/10.1016/j.media.2016.06.005</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0