Dataset - Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database

Christian Ledig 89b948dc2d ADD: example_seg.png 5 years ago
doc 89b948dc2d ADD: example_seg.png 5 years ago
ADNI_MALPEM_all_5074.csv e01f56f89a Initial Commit of Resources 5 years ago
ADNI_MALPEM_baseline_1069.csv e01f56f89a Initial Commit of Resources 5 years ago
ADNI_MALPEM_m12_802.csv e01f56f89a Initial Commit of Resources 5 years ago
ADNI_MALPEM_m24_532.csv e01f56f89a Initial Commit of Resources 5 years ago
LICENSE d11177248b UPDATE: LICENSE text 5 years ago
MALPEM_cross-sectional_seg138_5074.zip e01f56f89a Initial Commit of Resources 5 years ago
README.md 1e182b31ab UPDATE: README.md 5 years ago
datacite.yml 12e6917992 UPDATE: datacite.yml 5 years ago
features_CrossSect-5074_LongBLM12-802_LongBLM24-532.zip e01f56f89a Initial Commit of Resources 5 years ago
lut.csv 69d4c273b5 ADD: lookup table for segmentations (138 regions) 5 years ago
pincram_bin_brain_masks_5074.zip e01f56f89a Initial Commit of Resources 5 years ago

README.md

Readme

This repository contains data resources accompanying the article:

C. Ledig, A. Schuh, R. Guerrero, R. Heckemann, D. Rueckert "Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database", Scientific Reports, 2018.

In this article, we employed a recently validated method (MALPEM) for robust cross-sectional and longitudinal segmentation of MR brain images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Specifically, we segmented 5074 MR brain images into 138 anatomical regions and extracted time-point specific structural volumes and volume change during follow-up intervals of 12 or 24 months.

The work was done in the BioMedIA group at Imperial College London, UK.

Citation

Please cite as:

@article{Ledig2018,
  title={Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database},
  author={Ledig, Christian and Schuh, Andreas and Guerrero, Ricardo and Heckemann, Rolf and Rueckert, Daniel},
  journal={Scientific Reports},
  year={2018},
  publisher={Nature Publishing Group}
}

File Description

Processed Images from the ADNI cohort

Features

  • All extracted cross-sectional (structural volumes, asymmetry) and longitudinal (volume change rate) features and selected clinical information (e.g. disease labels). Note: Not all of those features have been used in the manuscript. Please, refer to the paper for details. [features_CrossSect-5074_LongBLM12-802_LongBLM24-532.zip]

Segmentations / Brain masks

License

The data in this repository is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International Public License. See the accompanying license file for details. The license does not allow usage of this data for commercial applications. This restriction is derived from the license of the Neuromorphometrics atlases (CC BY-NC).

Methodology

Multi-Atlas Label Propagation with Expecation-Maximisation based refinement (MALPEM) including pincram brain extraction is publicly available on github: [MALPEM]

We are working on releasing the actual source code of MALPEM within [MIRTK]

References

Framework and cross-sectional segmentation [paper]

C. Ledig, R. A. Heckemann, A. Hammers, J. C. Lopez, V. F. J. Newcombe, A. Makropoulos, J. Loetjoenen, D. Menon and D. Rueckert, "Robust whole-brain segmentation: Application to traumatic brain injury", Medical Image Analysis, 21(1), pp. 40-58, 2015.

Longitudinal segmentation [paper]

C. Ledig, W. Shi, A. Makropoulos, J. Koikkalainen, R. A. Heckemann, A. Hammers, J. Lötjönen, and D. Rueckert, "Consistent and robust 4D whole-brain segmentation: application to traumatic brain injury", Proceedings of ISBI 2014, pp. 673-676, 2014

Brain extraction [paper]

R. Heckemann, C. Ledig, K. R. Gray, P. Aljabar, D. Rueckert, J. V. Hajnal, and A. Hammers, "Brain extraction using label propagation and group agreement: pincram", PLoS ONE, 10(7), pp. e0129211, 2015.

Acknowledgements

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database [link]. As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: [link]

datacite.yml
Title Data for article 'Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database'
Authors Ledig,Christian;Imperial College London, Department of Computing, London, SW7 2AZ, UK;0000-0003-4862-3138
Schuh,Andreas;Imperial College London, Department of Computing, London, SW7 2AZ, UK;0000-0002-8214-116X
Guerrero,Ricardo;Imperial College London, Department of Computing, London, SW7 2AZ, UK
Heckemann,Rolf A.;MedTech West, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden;0000-0003-3582-3683
Rueckert,Daniel;Imperial College London, Department of Computing, London, SW7 2AZ, UK
Description Data derived from 5074 images from the ADNI cohort: - structural segmentations (138 regions, MALPEM); - binary brain masks (pincram); - features (volumes, asymmetry, atrophy rates) and disease labels; - lists of processed images Data accompanying the article: C. Ledig, A. Schuh, R. Guerrero, R. Heckemann, D. Rueckert, "Structural brain imaging in Alzheimer's disease and mild cognitive impairment: biomarker analysis and shared morphometry database", Scientific Reports, 2018.
License CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/legalcode.txt)
References
Funding Seventh Framework Programme (European Union Seventh Framework Programme), 611005
Innovate UK, 101685
Keywords Neuroscience
Biomarkers
Alzheimer's disease
Brain imaging
Magnetic resonance imaging
Resource Type Dataset