Deep Learning in MR Image Processing
Investigative Magnetic Resonance Imaging
;
: 81-99, 2019.
Artículo
en Inglés
| WPRIM
| ID: wpr-764174
ABSTRACT
Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Asunto principal:
Procesamiento de Imagen Asistido por Computador
/
Proteínas del Sistema Complemento
/
Imagen por Resonancia Magnética
/
Mejoramiento de la Calidad
/
Aprendizaje Automático
/
Aprendizaje
Idioma:
Inglés
Revista:
Investigative Magnetic Resonance Imaging
Año:
2019
Tipo del documento:
Artículo
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