MRI IMAGE RECONSTRUCTION VIA NEW K-SPACE SAMPLING SCHEME BASED ON SEPARABLE TRANSFORM

被引：0
|
作者：
Oliaiee, Ashkan [1 ]
Ghaffari, Aboozar [1 ]
Fatemizadeh, Emad [1 ]
机构：
[1] Sharif Univ Technol, Dept Elect Engn, Biomed Signal & Image Proc Lab BiSIPL, Tehran, Iran
来源：
2013 8TH IRANIAN CONFERENCE ON MACHINE VISION & IMAGE PROCESSING (MVIP 2013) | 2013年
关键词：
Magnetic Resonance Imaging(MRI); Sparsity; 2D-Compressed Sensing; Wavelet Transform; 2D-SL0; Algorithm; SPARSE DECOMPOSITION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Reducing the time required for MRI, has taken a lot of attention since its inventions. Compressed sensing (CS) is a relatively new method used a lot to reduce the required time. Usage of ordinary compressed sensing in MRI imaging needs conversion of 2D MRI signal (image) to 1D signal by some techniques. This conversion of the signal from 2D to 1D results in heavy computational burden. In this paper, based on separable transforms, a method is proposed which enables the usage of CS in MRI directly in 2D case. By means of this method, imaging can be done faster and with less computational burden.
引用
收藏
页码：127 / 130
页数：4
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