Radiomics and Deep Learning: Hepatic Applications
Korean Journal of Radiology
;
: 387-401, 2020.
Artículo
en Inglés
| WPRIM
| ID: wpr-811004
ABSTRACT
Radiomics and deep learning have recently gained attention in the imaging assessment of various liver diseases. Recent research has demonstrated the potential utility of radiomics and deep learning in staging liver fibroses, detecting portal hypertension, characterizing focal hepatic lesions, prognosticating malignant hepatic tumors, and segmenting the liver and liver tumors. In this review, we outline the basic technical aspects of radiomics and deep learning and summarize recent investigations of the application of these techniques in liver disease.
Texto completo:
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Índice:
WPRIM (Pacífico Occidental)
Idioma:
Inglés
Revista:
Korean Journal of Radiology
Año:
2020
Tipo del documento:
Artículo
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