The aim of this chapter is to offer an overview of the wide range of radiomics and machine learning applications that have been proposed for renal cell carcinoma (RCC) imaging. After describing the epidemiological, clinical, and pathological features of RCC, we explore the crucial role of imaging in the diagnosis, characterization, and follow-up of this disease.
Computed tomography and magnetic resonance imaging machine learning applications for renal cell carcinoma / Guerriero, Elvira; Stanzione, Arnaldo; Ugga, Lorenzo; Cuocolo, Renato. - (2022), pp. 1-21. [10.1088/978-0-7503-3595-9ch3]
Computed tomography and magnetic resonance imaging machine learning applications for renal cell carcinoma
Stanzione, Arnaldo;Ugga, Lorenzo;Cuocolo, Renato
2022
Abstract
The aim of this chapter is to offer an overview of the wide range of radiomics and machine learning applications that have been proposed for renal cell carcinoma (RCC) imaging. After describing the epidemiological, clinical, and pathological features of RCC, we explore the crucial role of imaging in the diagnosis, characterization, and follow-up of this disease.File in questo prodotto:
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