A REVIEW PAPER ON SYNOPSIS FOR DENOISING MULTI-CHANNEL IMAGES IN PARALLEL MRI BY LOW RANK MATRIX DECOMPOSITION AND LPG PCA
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.4, No. 4)Publication Date: 2015-04-30
Authors : Er. Mandeep Sandhu;
Page : 565-569
Keywords : Denoising; Low rank matrix decomposition; Multi-channel coil; parallel MRI (pMRI); Local Pixel Grouping Technique; Principal Component Analysis (PCA).;
Abstract
Parallel magnetic resonance imaging has emerged as an effective means for high-speed imaging in various applications. The reconstruction of parallel magnetic resonance imaging (pMRI) data can be a computationally demanding task. Signal-to-noise ratio is also a concern, especially in high-resolution imaging. We present a patchwise Denoising method for pMRI by exploiting the rank deficiency of multichannel images. For each processed patch and pixel, similar patches are searched with pixel in spatial domain and throughout all coil elements, and arranged in appropriate matrix forms. Then, noise and aliasing artifacts are removed from the structured matrix by applying sparse and low rank matrix decomposition method with Local Pixel Grouping using Principal Component Analysis (PCA). The proposed method has been validated using both phantom and in vivo brain data sets, producing encouraging results. Specifically, the method can effectively remove both noise and residual aliasing artifact from pMRI reconstructed noisy images, and produce higher peak signal noise rate (PSNR) and structural similarity index matrix (SSIM) than other state-of-the-art Denoising methods. The Denoising of pMRI is implemented using Image Processing Toolbox. This work has been tested and found suitable for its purpose. For the implementation of this proposed work we use the Matlab software.
Other Latest Articles
- A NEW METHOD FOR POPULATION FORECASTING BASED ON FUZZY TIME SERIES WITH HIGHER FORECAST ACCURACY RATE
- EFFICIENT DE-NOISING PERFORMANCE OF A COMBINED ALGORITHM OF “TRANSLATION INVARIANT (TI) WAVELETS AND INDEPENDENT COMPONENT ANALYSIS” OVER “TI WAVELETS” FOR SPEECH-AUDITORY BRAINSTEM RESPONSES
- PWM CONTROL CHOPPER FED CLOSED LOOP DRIVE FOR DC MOTOR USING MICROCONTROLLER
- WEIGHT LOSS CORROSION STUDIES OF ALUMINIUM-7075 ALLOY REINFORCED WITH SILICON CARBIDE PARTICULATES COMPOSITES IN ACID CHLORIDE MEDIUM
- CONTROLLING PC THROUGH MOBILE PHONE
Last modified: 2015-05-07 20:05:46