NDLI: Fast and accurate compressed sensing model in magnetic resonance imaging with median filter and split Bregman method

Content Provider	IET Digital Library
Author	Yang, Yunyun Qin, Xuxu Wu, Boying
Abstract	Magnetic resonance (MR) images have great importance to assist doctors in diagnosing diseases, however, the long MR images scan duration remains the primary obstacle in clinical medicine. Compressed sensing reconstructed technique in MR imaging (CS-MRI) makes it possible to reconstruct a faithful MR image from very few measurements data, which helps to reduce the scan time. The purpose of this study is to improve the accuracy and efficiency of the CS-MRI. The authors propose a fast compressed sensing reconstruction model for MR images that can alleviate the aliasing artefacts that come from the reconstruction process by jointly minimising a total variation term, a fitting data term and a median filter term. Moreover, they accelerate the proposed algorithm by applying the split Bregman method to solve the proposed model. Then, the proposed model is applied to reconstruct a large number of MR images. They also compare the performance of the proposed model with another model. It can be observed from the experimental results that the proposed model has shown higher precision in reconstructing image quality and much more efficiency than the other one. Additionally, they also give a discussion on how to choose proper parameters in the proposed model to obtain more satisfactory results.
Starting Page	1
Ending Page	8
Page Count	8
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5173
Journal	IET Image Processing
Publisher Date	2018-09-17
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Accurate Compressed Sensing Model Biology And Medical Computing Biomedical MRI Clinical Medicine Compressed Sensing Computer Vision And Image Processing Technique CS-MRI Diagnosing Diseases Diseases Faithful MR Image Fast Compressed Sensing Reconstruction Model Fitting Data Term Image Denoising Image Quality Image Reconstruction Iterative Method Long MR Image Scan Duration Magnetic Resonance Image Magnetic Resonance Imaging Measurement Data Median Filter Median Filter Term Medical Image Processing Minimisation MR Imaging Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Primary Obstacle Reconstruction Process Scan Time Split Bregman Method Total Variation Term
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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