Motion Correction for Brain MRI Using Deep Learning and a Novel Hybrid Loss Function

Purpose: Motion-induced magnetic resonance imaging (MRI) artifacts can deteriorate image quality and reduce diagnostic accuracy, but motion by human subjects is inevitable and can even be caused by involuntary physiological movements. Deep-learning-based motion correction methods might provide a sol...

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Autors principals:	Lei Zhang, Xiaoke Wang, Michael Rawson, Radu Balan, Edward H. Herskovits, Elias R. Melhem, Linda Chang, Ze Wang, Thomas Ernst
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-05-01
Col·lecció:	Algorithms
Matèries:	MRI motion correction deep learning brain
Accés en línia:	https://www.mdpi.com/1999-4893/17/5/215
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