Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

Pomponio, Raymond; Erus, Güray; Habes, Mohamad; Doshi, Jimit; Srinivasan, Dhivya; Mamourian, Elizabeth; Bashyam, Vishnu; Nasrallah, Ilya M.; Satterthwaite, Theodore D.; Fan, Yong; Launer, Lenore J.; Masters, Colin L.; Maruff, Paul; Zhuo, Chuanjun; Völzke, Henry; Johnson, Sterling C.; Fripp, Jürgen; Koutsouleris, Nikolaos; Wolf, Daniel H.; Gur, Raquel E.; Gur, Ruben C.; Morris, John C.; Albert, Marilyn S.; Grabe, Hans J.; Resnick, Susan M.; Bryan, R. Nick; Wolk, David A.; Shinohara, Russell T.; Shou, Haochang; Davatzikos, Christos

doi:10.1016/j.neuroimage.2019.116450

articleNeuroImageDec 9, 2019HYBRID OA

Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan

RPRaymond Pomponio GEGüray Erus MHMohamad Habes JDJimit Doshi DSDhivya Srinivasan

University of Pennsylvania · National Institute on Aging · +14 more institutions

PubMed

Indexed incrossrefdoajpubmed

Abstract

As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain…

Citation impact

528

total citations

FWCI: 20.55
Percentile: 100%
References: 65

Citations per year

Authors

30

Topics & keywords

Topics

Keywords

Neuroimaging
Harmonization
Data science
Computer science
Pooling
Big data
Brain atlas
Visualization

No related works found for this paper.