Improved k-t PCA Algorithm Using Artificial Sparsity in Dynamic MRI

The k-t principal component analysis (k-t PCA) is an effective approach for high spatiotemporal resolution dynamic magnetic resonance (MR) imaging. However, it suffers from larger residual aliasing artifacts and noise amplification when the reduction factor goes higher. To further enhance the perfor...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yiran, Chen, Zhifeng, Wang, Jing, Yuan, Lixia, Xia, Ling, Liu, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540396/
https://www.ncbi.nlm.nih.gov/pubmed/28804506
http://dx.doi.org/10.1155/2017/4816024

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540396/
https://www.ncbi.nlm.nih.gov/pubmed/28804506
http://dx.doi.org/10.1155/2017/4816024

Ejemplares similares