Reconstruction of Undersampled Big Dynamic MRI Data Using Non-Convex Low-Rank and Sparsity Constraints

Dynamic magnetic resonance imaging (MRI) has been extensively utilized for enhancing medical living environment visualization, however, in clinical practice it often suffers from long data acquisition times. Dynamic imaging essentially reconstructs the visual image from raw (k,t)-space measurements,...

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Detalles Bibliográficos
Autores principales: Liu, Ryan Wen, Shi, Lin, Yu, Simon Chun Ho, Xiong, Naixue, Wang, Defeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375795/
https://www.ncbi.nlm.nih.gov/pubmed/28273827
http://dx.doi.org/10.3390/s17030509

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375795/
https://www.ncbi.nlm.nih.gov/pubmed/28273827
http://dx.doi.org/10.3390/s17030509

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