Published September 11, 2021 | Version v1
Dataset Open

Dataset : Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps

Creators

  • 1. Centre for Complexity Science, Imperial College London, London, United Kingdom
  • 2. Department of Physics, Imperial College London, London, United Kingdom
  • 3. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
  • 4. ElectroCardioMaths Programme, Imperial Centre for Cardiac Engineering, Faculty of Medicine, Imperial College London, London, United Kingdom

Description

  • The three files in the dataset are:

1) Healthy Sheep Atria Fibre Orientation Dataset 300µm

2) Heart Failure Sheep Atria Fibre Orientation Dataset 300µm

3) Human Atria Fibre Orientation Dataset 330µm

  • Data is stored as numpy binary files. Given below is an example .py script to open the flat datasets:

    import numpy as np
    data = np.load("Human_330um.npy")

  • Volume and fibre orientation dataset stored in flat format as given below:

    i, j, k, v1, v2, v3, ...  repeated for each voxel          

where (i, j, k) are voxel coordinates and (v1, v2, v3) are vector components corresponding to fibre orientation within that voxel.

Notes

The code used to generate the spatial networks is available at : github.com/JamesAlecColeman/reentrySpatialNetworks

Files

Files (1.6 GB)

Name Size Download all
md5:a4c7502b0bfcd6971c364186e782843d
338.3 MB Download
md5:7349cc001c92ae6130ea4e7011ead3c0
306.6 MB Download
md5:520681a6559bebebc9dec613068ea70d
975.9 MB Download