作者: Benedikt A. Poser , David G. Norris
DOI: 10.1016/J.NEUROIMAGE.2009.01.007
关键词: Pattern recognition 、 Sensitivity (control systems) 、 Image quality 、 Filter (signal processing) 、 Artificial intelligence 、 Signal 、 Mri studies 、 Contrast (vision) 、 Image resolution 、 Echo (computing) 、 Computer science 、 Distortion
摘要: Abstract Functional MRI studies on humans with BOLD contrast are increasingly performed at high static magnetic field in order to exploit the increased sensitivity. The downside of high-field fMRI using gradient-echo echo-planar imaging (GE-EPI) method is that images typically very strongly affected by image distortion and signal loss. It has been demonstrated 1.5 T 3 T artifacts can be reduced functional sensitivity simultaneously use parallel-accelerated multi-echo EPI. Using measurements an activation study a cognitive Stroop task experiment ( N = 7) we here investigate potential this 7 T. main findings are: (a) quality compared conventional acquisition scheme drastically improved; (b) according CNR estimations average increases 6.1 ± 4.3% 13.9 ± 5.5% for unweighted CNR-weighted echo summation, respectively; (c) both changes data do not exhibit pronounced dependence TE. consequence (d) practice performance simple summation comparable based filter. Finally, (e) temporal noise observed different time courses correlated, thus explaining why advantageous. results typical spatial resolution show EPI leads considerable artifact reduction gains, making it superior GE-EPI