AUTHOR=Wang Zijie , Zhang Xiaofei , Wang Xinning , Li Jianfei , Zhang Yuhao , Zhang Tianwei , Xu Shang , Jiao Wei , Niu Haitao 

TITLE=Deep learning techniques for imaging diagnosis of renal cell carcinoma: current and emerging trends

JOURNAL=Frontiers in Oncology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1152622

DOI=10.3389/fonc.2023.1152622

ISSN=2234-943X

ABSTRACT=Medical imaging plays an important role in the early detection of renal cell carcinoma (RCC), as well as in the monitoring and evaluation of RCC during treatment. The most commonly used technologies such as contrast enhanced computed tomography (CECT), ultrasound and magnetic resonance imaging (MRI) are now digitalized, allowing deep learning to be applied to them. Deep learning is one of the fastest growing fields in the direction of medical imaging, with rapidly emerging applications that have changed the traditional medical treatment paradigm. With the help of deep learning-based medical imaging tools, clinicians can diagnose and evaluate renal tumors more accurately and quickly. This paper describes the application of deep learning-based imaging techniques in RCC assessment and provides a comprehensive review.