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Investigative magnetic resonance imaging, 2019, Vol.23 (2), p.81-99
Erscheinungsjahr
2019
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
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.
Sprache
Koreanisch
Identifikatoren
ISSN: 2384-1095
eISSN: 2384-1109
Titel-ID: cdi_kisti_ndsl_JAKO201919362371921
Format
–
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