Siemens Aktiengesellschaft

Cai Xia Fu

Jian Wang

Ke Wang

Bi Da Zhang

Hua Zhu

Guo Li

Jian Li

In a method and apparatus for magnetic resonance imaging, a flip angle and/or inversion time of a spectrum suppression pulse is calculated according to a steady state condition of a longitudinal magnetization component of a spectrum composition suppressed by the spectrum suppression pulse and a zero crossing point condition of the longitudinal magnetization component. Raw magnetic resonance image data are acquired by applying a magnetic resonance imaging sequence that includes the spectrum suppression pulse provided with the flip angle and/or the inversion time.

Method and apparatus for magnetic resonance imaging

In a method and device for side-band suppression, a positive eddy current correction factor and negative eddy current correction factor are determined and scanning N/2 times by a positive gradient takes place, and the positive gradient scanning signal is collected during each scan. Scanning N/2 times by a negative gradient also takes place, and the negative gradient scanning signal is collected during each scan. N is an even number. An eddy current correction of the N/2 positive gradient scanning signals collected according to the positive eddy current correction factor is performed as an eddy current correction of the N/2 negative gradient scanning signals collected according to the negative eddy current correction factor. The side-band suppressed spectrum signal according to the N/2 positive gradient scanning signals that have undergone the eddy current correction is calculated, as is the N/2 negative gradient scanning signals that have undergone the eddy current correction. The method and device according to the present invention can effectively suppress the side band.

Side-band suppression method and side-band suppression device

In a method and apparatus for improving the brightness uniformity in an image, signals are acquired using a radio frequency receiving coil, and noise in the acquired signals is normalized so as to produce an image, then the brightness of various pixels in the image is determined according to the sensitivity of the radio frequency receiving coil. The brightness of the image is then made uniform by compensating the brightness of the various pixels in the image.

Method and apparatus for improving brightness uniformity in an image

The invention discloses a method for calculating the signal-to-noise ratio (SNR) in parallel acquisition image reconstruction, comprising: determining a reconstruction expression for a linear operation of the image reconstruction; determining a weighted coefficient according to the reconstruction expression; calculating the SNR according to the weighted coefficient and the raw data. The SNR not only is relevant to the geometric shape and position of the coils, but also is influenced by the reconstruction method and the sampling mode. The SNR is calculated based on contribution of the raw data at positions in the reading direction from all the phase-coding lines in all acquisition channels. It reflects more precisely the loss of the SNR in the parallel acquisition image reconstruction, especially the changes in the SNR caused by the number of the reference lines combined during the reconstruction.

Method for calculating signal-to-noise ratio in parallel acquisition image reconstruction

The invention discloses a method and an apparatus for reconstructing a parallel-acquired image, comprising: generating reconstruction data by combining uniformly under-sampled data and low-frequency fully-sampled data in MRI K-space according to a hybrid sampling mode; calculating the sensitivity distribution of a coil according to said low-frequency fully-sampled data; and reconstructing an image according to the reconstruction data, the coil's sensitivity distribution and the hybrid sampling mode. The signal to noise ratio of the reconstructed image is effectively improved by using the reconstruction data combined with the low-frequency fully-sampled data in reconstructing the image since the low-frequency fully-sampled data contains more useful information.

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Shenzhen, China

Cai Xia Fu