Read more
This book, endorsed by EuSoMII, provides clinicians, researchers and scientists a useful handbook to navigate the intricate landscape of data harmonization, as we embark on a journey to improve the reproducibility, robustness and generalizability of multi-centric real-world data radiomic studies.
In these pages, the authors delve into the foundational principles of radiomics and its far-reaching implications for precision medicine. They describe the different methodologies used in extracting quantitative features from medical images, the building blocks that enable the transformation of images into actionable predictions. This book sweeps from understanding the basis of harmonization to the implementation of all the knowledge acquired to date, with the aim of conveying the importance of harmonizing medical data and providing a useful guidance to enable its applicability and the future use of advanced radiomics-based models in routine clinical practice.
As authors embark on this exploration of data harmonization in radiomics, they hope to ignite discussions, foster new ideas, and inspire researchers, clinicians, and scientists alike to embrace the challenges and opportunities that lie ahead. Together, they elevate radiomics as a reproducible technology and establish it as an indispensable and actionable tool in the quest for improved cancer diagnosis and treatment.
List of contents
Era of AI quantitative imaging.- Principles of image formation in the different modalities.- How to extract radiomic features from the image?.- Facts and needs to improve Radiomics reproductibility.- What is harmonization and how does it differ from standardization?.- Harmonization in the image domain.- Harmonization across MRI.- Harmonization in the features domain.- Selection of the optimal harmonization method(s) for the problem under study.- Conclusions.
About the author
Ángel Alberich-Bayarri. Telecommunications Engineer with specialisation in electronics by the Technical University of Valencia and PhD in Biomedical Engineering for his research on the application of advanced image processing techniques to magnetic resonance imaging. Founder and CEO of Quibim (Quantitative Imaging Biomarkers in Medicine), company dedicated to the advanced analysis of medical images using artificial intelligence. He is the author of more than 90 scientific articles in prestigious international journals and inventor of 5+ patents. He is also the author of more than 100 communications to international congresses, editor of international books and author of 20+ book chapters. He has participated in a high number of international research projects and clinical trials. He is an active member of several scientific societies, among which stands out his participation as a member of the Board of Directors of the European Society of Medical Imaging Informatics (EUSOMII).
Fuensanta Bellvís Bataller, MS. Biomedical engineer specialized in Information and Communication Technologies. She has extensive experience in the field of companion diagnostics and medical imaging. She started her career in a start-up to develop a multidimensional tissue signature for brain tumors and worked as a software engineer optimizing the hospital management system tool used in her region. She started at Quibim as R&D engineer and is currently the VP of Clinical Studies, responsible of the department that manages clinical trials, observational studies and research projects in collaboration with biopharmaceutical companies and academic and research institutions, mainly in the areas of oncology/immunotherapy, rheumatology and neurology.
