An inverse method to design RF coil arrays optimized for SENSE imaging.
A new method to design MRI RF coils that are optimized for SENSE (sensitivity encoding) imaging is introduced. In this approach, the inverse problem was solved where the surface current density distribution on a coil former was calculated to maximize the SNR(sense) within a volume of interest (VOI). For that purpose, an analytic relationship was formulated between the SNR(sense) and surface current density on the coil former. The SNR at pixel rho in a SENSE-MR image, SNR(sense,rho), is inversely proportional to the g-factor: therefore, the g-factor was formulated in terms of the B1 distribution of the coils. Then, by specifying the geometry of the desired coil former and using a finite element mesh (FEM), the surface current distribution was calculated to maximize the SNR(sense), by minimizing (1/SNR(sense)) in the VOI using a least squares procedure. A simple two-coil array was designed and built to test the method and phantom images were collected. The results show that the new coil design method yielded better uniformity and SNR in SENSE images compared to those of standard coils.
Muftuler
L Tugan
LT
Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, Irvine, CA 92697-5020, USA. tugan.muftuler@uci.edu
Chen
Gang
G
Nalcioglu
Orhan
O
D000465:Algorithms; D016477:Artifacts; D003952:Diagnostic Imaging / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D016018:Least-Squares Analysis; D008432:Mathematical Computing; D015233:Models, Statistical; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D011846:Radio Waves; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted