Pre- and post-surgery brain tumor multimodal magnetic resonance imaging data optimized for large scale computational modelling

Hannelore Aerts; Nigel Colenbier; Hannes Almgren; Thijs Dhollander; Javier Rasero Daparte; Kenzo Clauw; Amogh Johri; Jil Meier; Jessica Palmer; Michael Schirner; Petra Ritter; Daniele Marinazzo

doi:10.1038/s41597-022-01806-4

Scientific Data (Nov 2022)

Pre- and post-surgery brain tumor multimodal magnetic resonance imaging data optimized for large scale computational modelling

Hannelore Aerts,
Nigel Colenbier,
Hannes Almgren,
Thijs Dhollander,
Javier Rasero Daparte,
Kenzo Clauw,
Amogh Johri,
Jil Meier,
Jessica Palmer,
Michael Schirner,
Petra Ritter,
Daniele Marinazzo

Affiliations

Hannelore Aerts: Department of Data Analysis, Ghent University
Nigel Colenbier: Department of Data Analysis, Ghent University
Hannes Almgren: Department of Data Analysis, Ghent University
Thijs Dhollander: Murdoch Children’s Research Institute | MCRI Research Group for Developmental Imaging
Javier Rasero Daparte: CoAx Lab, Carnegie Mellon University
Kenzo Clauw: Department of Data Analysis, Ghent University
Amogh Johri: Indraprastha Institute of Information Technology
Jil Meier: Berlin Institute of Health at Charité – Universitätsmedizin Berlin
Jessica Palmer: Berlin Institute of Health at Charité – Universitätsmedizin Berlin
Michael Schirner: Berlin Institute of Health at Charité – Universitätsmedizin Berlin
Petra Ritter: Berlin Institute of Health at Charité – Universitätsmedizin Berlin
Daniele Marinazzo: Department of Data Analysis, Ghent University

DOI: https://doi.org/10.1038/s41597-022-01806-4
Journal volume & issue: Vol. 9, no. 1
pp. 1 – 10

Abstract

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Measurement(s) BOLD signal • Diffusion Anisotropy Technology Type(s) Functional Magnetic Resonance Imaging • Diffusion Weighted Imaging Factor Type(s) Surgery Sample Characteristic - Organism Homo sapiens

Published in Scientific Data

ISSN: 2052-4463 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/sdata/

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