[Inverse iterative correction for translational motion artifact of magnetic resonance imaging based on histogram entropy minimization].
During the acquisition of a magnetic resonance images (MRI), blurring and ghosting artifacts caused by the patient's motion can seriously affect the result of diagnosis. A novel automatic post-processing strategy, inverse iterative correction (IIC), has been developed to suppress MRI artifacts due to the object's in-plane rigid-body motion. By means of the proposed histogram-based entropy function, IIC method uses two successive steps to reduce the simulated motion artifacts: first, the inverse phase errors are added to all possible simulated patient's motion directions, and in the second step, the actual directions and displacement from the patient's motion are estimated to properly correct the phase, hence remove the artifacts after searching all the trial directions. To verify its feasibility, the proposed method was used to reduce rigid-motion artifacts due to simulated motion in MRI images. The experimental results showed that the new algorithm significantly outperforms over the entropy auto-focus compensation algorithm on the quality of corrections for the motion artifacts and computational cost.
Jiang
Gui-ping
GP
Key Lab for Medical Image Processing, Southern Medical University, Guangzhou 510515, China. qzjiang@263.net
Chen
Wu-fan
WF
Hou
Zhen-song
ZS
D000465:Algorithms; D016477:Artifacts; D006801:Humans; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009068:Movement; D019047:Phantoms, Imaging