Work

The 2024 MRSI Data Processing and Quantification Challenge Synthetic Dataset

Year: 2026

Type: dataset

Abstract: A simulated 3 T brain FID-MRSI dataset with known ground-truth metabolite maps, created for the 2024 MRSI Data Processing and Quantification Challenge. Subject-specific simulations were generated from anatomical images and B0 field maps derived from Human Connectome Project (WU-Minn HCP) subjects. The dataset comprises 24 training and 8 testing subject-level datasets (five for sub-challenge 1, with water and lipid nuisance signals; three for sub-challenge 2, without). Each provides contaminated FID-MRSI data, a T1-weighted anatomical image, a B0 map, a brain mask, ground-truth metabolite amplitude maps, and the separable component signals. Data are distributed in NIfTI-MRS and MATLAB (.mat) formats; see README.txt. Derived in part from WU-Minn HCP data and distributed under the WU-Minn HCP Consortium Open Access Data Use Terms.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.21890221

Authors: LaMaster, John, Merkofer, Julian P., van de Sande, Dennis, Soher, Brian, Strasser, Bernhard, Ma, Chao

Institutions: Technical University of Munich, University Medical Center Utrecht, Eindhoven University of Technology, Duke Medical Center, Medical University of Vienna, Yale University

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

Open Access status: green

OpenAlex ID: W7204807375

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