EIBALL 19 - Imaging data harmonisation for reproducible imaging biomarkers and radiomics
March 7, 12:30 - 13:30 CET
5 min
Chairperson's introduction
15 min
Why is data harmonisation important for imaging biomarkers and radiomics?
To learn the key concepts and challenges in using imaging biomarkers and radiomics across multi-centre studies.
To appreciate how variability in imaging protocols and acquisition impacts reproducibility and clinical utility of quantitative imaging biomarkers and radiomics.
To understand the role of data harmonisation in enabling reliable, generalisable and clinically relevant analysis.
15 min
Strategies for harmonisation of imaging data
To learn the main methodological approaches for harmonising imaging data across scanners, protocols and institutions.
To appreciate the advantages and limitations of preprocessing, standardisation and statistical correction techniques.
To understand how harmonisation strategies can be applied in research and clinical practice.
15 min
Artificial intelligence (AI) approaches to imaging data harmonisation
To learn about current AI/ML-based techniques for harmonising imaging data.
To appreciate the potential of AI/ML to address complex sources of variability in multi-centre imaging data.
To understand how AI-driven harmonisation can support more accurate and robust imaging biomarker discovery and validation.
10 min
Panel discussion: What are the key challenges for implementing data harmonisation in real-world clinical settings?