Cargando…
Compressed Sensing-Based MRI Reconstruction Using Complex Double-Density Dual-Tree DWT
Undersampling k-space data is an efficient way to speed up the magnetic resonance imaging (MRI) process. As a newly developed mathematical framework of signal sampling and recovery, compressed sensing (CS) allows signal acquisition using fewer samples than what is specified by Nyquist-Shannon sampli...
Autores principales: | Zhu, Zangen, Wahid, Khan, Babyn, Paul, Yang, Ran |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3690259/ https://www.ncbi.nlm.nih.gov/pubmed/23840199 http://dx.doi.org/10.1155/2013/907501 |
Ejemplares similares
-
Improved Compressed Sensing-Based Algorithm for Sparse-View CT Image Reconstruction
por: Zhu, Zangen, et al.
Publicado: (2013) -
Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform
por: Chen, Shanshan, et al.
Publicado: (2017) -
An Efficient Methodology for Brain MRI Classification Based on DWT and Convolutional Neural Network
por: Fayaz, Muhammad, et al.
Publicado: (2021) -
Dual-Channel Reconstruction Network for Image Compressive Sensing
por: Zhang, Zhongqiang, et al.
Publicado: (2019) -
An Improved Image Compression Algorithm Using 2D DWT and PCA with Canonical Huffman Encoding
por: Ranjan, Rajiv, et al.
Publicado: (2023)