A super-resolution framework for 3-D high-resolution and high-contrast imaging using 2-D multislice MRI.
A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.
Shilling
Richard Z
RZ
Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332 USA. richard.shilling@gatech.edu
Robbie
Trevor Q
TQ
Bailloeul
Timothée
T
Mewes
Klaus
K
Mersereau
Russell M
RM
Brummer
Marijn E
ME
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D012984:Software