Full exploitation of high dimensionality in brain imaging

The JPND working group statement and findings

Journal Article (2019)
Author(s)

Hieab H.H. Adams (Erasmus MC)

Gennady Roshchupkin (Erasmus MC)

Charles DeCarli (University of California)

Barbara Franke (Radboud Universiteit Nijmegen)

H. J. Grabe (Greifswald University)

Mohamad Habes (University of Pennsylvania)

Neda Jahanshad (University of Southern California)

S. E. Medland (Queensland Institute of Medical Research)

WJ Niessen (TU Delft - ImPhys/Quantitative Imaging, Erasmus MC)

More authors (External organisation)

Research Group
ImPhys/Quantitative Imaging
Copyright
© 2019 Hieab H.H. Adams, Gennady V. Roshchupkin, Charles DeCarli, Barbara Franke, Hans J. Grabe, Mohamad Habes, Neda Jahanshad, Sarah E. Medland, W.J. Niessen, More Authors
DOI related publication
https://doi.org/10.1016/j.dadm.2019.02.003
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Hieab H.H. Adams, Gennady V. Roshchupkin, Charles DeCarli, Barbara Franke, Hans J. Grabe, Mohamad Habes, Neda Jahanshad, Sarah E. Medland, W.J. Niessen, More Authors
Research Group
ImPhys/Quantitative Imaging
Volume number
11
Pages (from-to)
286-290
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Abstract

Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme–Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.