Published June 10, 2016 | Version v1
Dataset Open

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

  • 1. Division of Imaging Sciences and Biomedical Engineering, King’s College London, London, UK
  • 2. Centre for Medical Image Computing, University College London, London, UK
  • 3. Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK

Description

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:

  1. Acquisition of all sagittal slice positions covering the thorax and one coronal slice position acquired during a breath hold.
  2. Results of registration between adjacent sagittal slice positions [control point displacements (cpp) and displacement fields (dfs)]
  3. 40 dynamic acquisitions of each slice position also present in the breath-hold acquired during free breathing. 
  4. Results of registration of the dynamic acquisitions to the respective breath-holds slices (cpp's and dfs's). 

The data is divided into 4 zip files, each containing the data of one volunteer. The folder structure for each is as follows:

|-- bhs (breath hold data)
|   |-- images (images)
|   |   |-- cor
|   |   `-- sag
|   `-- mfs_slpos2slpos (registration results)
|       `-- sag
`-- dyn (dynamic free-breathing data)
    |-- images (images)
    |   |-- cor
    |   `-- sag
    `-- mfs_tpos2tpos (registration results)
        |-- cor
        `-- sag

Please, see our publication [1] for details on the acquisition sequence and registration used. 

--

[1]: CF Baumgartner, C Kolbitsch, JR McClelland, D Rueckert, AP King, Autoadaptive motion modelling for MR-based respiratory motion estimation, Medical Image Analysis (2016), http://dx.doi.org/10.1016/j.media.2016.06.005

Files

volunteerA.zip

Files (2.3 GB)

Name Size Download all
md5:a1123d28c0fcbb5c016ddfc6fba0b8a8
566.6 MB Preview Download
md5:edbdb25fd7d07e481b1653d7e9f842f9
569.6 MB Preview Download
md5:ca2b0e69752eb66560b967d5d75a296b
562.6 MB Preview Download
md5:8f936fcbef746d775339393b1f9366a7
615.1 MB Preview Download

Additional details

Related works