ESMRMB 2025 focus topic: cycle of quality—from concept to clinical and scientific impact

Across the plenary and four educational sessions, the speakers explore how quality manifests at every stage of the MRI cycle: from acquisition and analysis, to algorithmic design, to harmonization, and ultimately, to research dissemination. [...]Bertrand Thirion (“AI and Harmonization: Standardizati...

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Veröffentlicht in:Magma (New York, N.Y.) Jg. 38; H. 3; S. 631 - 633
Hauptverfasser: Küstner, Thomas, Haast, Roy, Priovoulos, Nikos, Clement, Patricia, dos Santos, Daniel Pinto
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.07.2025
Springer Nature B.V
Schlagworte:
artefacts
Artificial intelligence
Authorship
Basic Science - Motion
Biomarkers
Biomedical Engineering and Bioengineering
Collaboration
Commentary
Computer Appl. in Life Sciences
Confounding (Statistics)
Design
Health Informatics
Imaging
Magnetic resonance imaging
Medicine
Medicine & Public Health
Noise measurement
Physiological effects
Protocol
Quality control
Quality standards
Radiology
Reproducibility
Scanners
Signal to noise ratio
Solid State Physics
Standardization
ISSN:1352-8661, 0968-5243, 1352-8661
Online-Zugang:Volltext
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Zusammenfassung:Across the plenary and four educational sessions, the speakers explore how quality manifests at every stage of the MRI cycle: from acquisition and analysis, to algorithmic design, to harmonization, and ultimately, to research dissemination. [...]Bertrand Thirion (“AI and Harmonization: Standardization for robust algorithms?”) tackles the interaction between AI and harmonization, asking whether harmonization should precede AI modeling or be embedded within it. Understanding and mitigating confounding factors”) introduces the multifactorial nature of qMRI confounds—ranging from physiological noise and scanner instabilities to the specific choice of fitting models and parameters. Task-based evaluations, artifact quantification, and visual integrity scores as alternatives or supplements to traditional measures like signal-to-noise ratio (SNR) are presented.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Commentary-1
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ObjectType-Correspondence-1
ISSN:1352-8661
0968-5243
1352-8661
DOI:10.1007/s10334-025-01272-0