Radiomics: Extracting more information from medical images using advanced feature analysis
2012 · European Journal of Cancer · 5,765 citations
https://doi.org/10.1016/j.ejca.2011.11.036
R
Ralph T. H. Leijenaar
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Ralph T. H. Leijenaar is an academic researcher from Maastricht University. The author has contributed to research in topics: Radiomics and Machine Learning in Medical Imaging & Advanced X-ray and CT Imaging & Medical Imaging Techniques and Applications. The author has an h-index of 47, co-authored 122 publications.
ORCID: 0000-0001-8642-9657Papers by this author
worksDecoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
2014 · Nature Communications · 4,967 citations
https://doi.org/10.1038/ncomms5006
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping
2020 · Radiology · 3,655 citations
https://doi.org/10.1148/radiol.2020191145
Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
2015 · Scientific Reports · 430 citations
https://doi.org/10.1038/srep11044
MRI-based radiomics in breast cancer: feature robustness with respect to inter-observer segmentation variability
2020 · Scientific Reports · 80 citations
https://doi.org/10.1038/s41598-020-70940-z
Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer
2020 · Scientific Reports · 78 citations
https://doi.org/10.1038/s41598-020-61297-4
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