Artificial intelligence, radiomics and other horizons in body composition assessment
| Autor: | Emanuele Neri, Michela Gabelloni, Simona Attanasio, Giuliana Restante, Giuseppe Guglielmi, Sara Maria Forte |
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| Rok vydání: | 2020 |
| Předmět: |
Radiomics
medicine.diagnostic_test business.industry Computer science Magnetic resonance imaging Computed tomography Review Article Artificial intelligence (AI) Body composition assessment 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine 030220 oncology & carcinogenesis Assessment methods medicine Radiology Nuclear Medicine and imaging Applications of artificial intelligence Personalized medicine Artificial intelligence business Composition (language) |
| Zdroj: | Quant Imaging Med Surg |
| ISSN: | 2223-4306 2223-4292 |
| Popis: | This paper offers a brief overview of common non-invasive techniques for body composition assessment methods, and of the way images extracted by these methods can be processed with artificial intelligence (AI) and radiomic analysis. These new techniques are becoming more and more appealing in the field of health care, thanks to their ability to treat and process a huge amount of data, suggest new correlations between extracted imaging biomarkers and traits of several diseases as well as lead to the possibility to realise an increasingly personalized medicine. The idea is to suggest the use of AI applications and radiomic analysis to search for features that may be extracted from medical images [computed tomography (CT) and magnetic resonance imaging (MRI)], and that may turn out to be good predictors of metabolic disorder diseases and cancer. This could lead to patient-specific treatments and management of several diseases linked with excessive body fat. |
| Databáze: | OpenAIRE |
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