Résumé
Computational medical imaging (or radiomics) is a recent and extremely promising discipline. It consists of computer analysis of medical images and translates them into complex quantitative data. This high-dimensional data allows a more in-depth characterization of the tumor phenotype. Radiomics has the advantage to be non-invasive, to evaluate the whole tumor and the spatial heterogeneity, and to allow monitoring of the tumor evolution over time. The ultimate goal of radiomics is to develop imaging biomarkers that provide medical decision support and also allow a better understanding of the cancer biology. We will present here the workflow used in radiomics, and present the potential of its use in lung cancers.
Titre traduit de la contribution | Computational medical imaging (radiomics): Principles and potential in onco-pneumology |
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langue originale | Français |
Pages (de - à) | 2S307-2S313 |
journal | Revue des Maladies Respiratoires Actualites |
Volume | 12 |
Numéro de publication | 2 |
Les DOIs | |
état | Publié - 1 oct. 2020 |
mots-clés
- Computational medical imaging
- Immunology
- Oncology
- Radiomics