We have been investigating functional MRI (fMRI) using Student
t-test analysis for selecting activated regions. This analysis is sensitive to the signal to noise ratio (SNR) level, so that a low SNR reduce the activated size. In this report we describe new analysis, a combination of Student
t-test analysis and signal change analysis. This combination of two analyses is less sensitive to the SNR level. Experiments of fMRI were performed using a 1.5-T prototype MRI system with local gradient coils. Healthy volunteers carried out a left-finger tapping task in these experiments. Clinical images were acquired using spin-echo sequence to identify the structure of the brains. Functional images were acquired using two sequences, echo-planar imaging (EPI) sequence and interleaved EPI (IEPI) sequence. Each imaging sequence had the following parameters: 1) EPI:
TE=15ms, data acquisition time=75ms, spatial resolution=4×2mm and temporal resolution=2s; and 2) IEPI:
TE=15ms, data acquisition time=75ms, spatial resolution=2×1mm, and temporal resolution=8s. The SNR of IEPI is about a quarter that of EPI. The activated regions were selected by using Student
t-test analysis and the combination of two analyses respectively. The activated size was calculated based on the number of pixels in the activated region and the pixel size. As a result of Student
t-test analysis the activated sizes of IEPI reduced to less than half those of EPI. But there were not a significant differences in the activated sizes estimated by the combination of two analyses between EPI and IEPI. We conclude that our proposed combination analysis method can estimate the size of the activated areas more precisely.
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