English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Magnetic Resonance Imaging (MRI) has been utilized broadly for clinical purposes to portray human anatomy due to its non-intrusive nature. The information acquisition method in MRI naturally picks up encoded signals (Fourier transformed) instead of pixel values and is called k-space information. Sparse reconstruction techniques can be executed in MRI for producing an image from fewer measurements. Compressive sensing (CS) technique samples the signals at a rate lower than traditional Nyquist’s rate and thereby reduces the data acquisition time in MRI. This paper investigates a new proposed sampling scheme along with radial sampling and 1D Cartesian variable density sampling. For various sampling percentages, subjective and quantitative analyses are carried out on the reconstructed Magnetic Resonance image. Experimental results depicts that the high sampling density near the center of k-space gives a better reconstruction of compressing sensing MRI.

international journal of innovative technology and exploring engineering

148 Published By: Blue Eyes Intelligence Engineering &amp; Sciences Publication Retrieval Number K12620981119/2019©BEIESP DOI: 10.35940/ijitee.K1262.0981119 Journal Website: www.ijitee.org Performance Evaluation of Total Variation based Compressed Sensing MRI for Different Sampling Patterns