DeepHarmony: A deep learning approach to contrast harmonization across scanner changes

Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibility between protocols and scanners. It has been shown that even when care is taken to standardize acquisitions, any changes in hardware, software, or protocol design can lead to differences in quanti...

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Vydané v:	Magnetic resonance imaging Ročník 64; s. 160 - 170
Hlavní autori:	Dewey, Blake E., Zhao, Can, Reinhold, Jacob C., Carass, Aaron, Fitzgerald, Kathryn C., Sotirchos, Elias S., Saidha, Shiv, Oh, Jiwon, Pham, Dzung L., Calabresi, Peter A., van Zijl, Peter C.M., Prince, Jerry L.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Netherlands Elsevier Inc 01.12.2019
Predmet:	Atrophy Brain - diagnostic imaging Brain - pathology Clinical Protocols Cohort Studies Contrast harmonization Deep learning Deep Learning - statistics & numerical data Humans Image Interpretation, Computer-Assisted - methods Longitudinal Studies Magnetic resonance imaging Magnetic Resonance Imaging - instrumentation Magnetic Resonance Imaging - methods Multiple Sclerosis - pathology Reproducibility of Results Deep learning Magnetic resonance imaging Contrast harmonization
ISSN:	0730-725X, 1873-5894, 1873-5894
On-line prístup:	Získať plný text
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