Doubling the sampling points in frequency encoding direction without expanding the scan time. The additional part is discarded after reconstruction.

See also Oversampling and Aliasing Artifact.

(SENSE) A MRI technique for relevant scan time reduction. The spatial information related to the coils of a receiver array are utilized for reducing conventional Fourier encoding. In principle, SENSE can be applied to any imaging sequence and k-space trajectories. However, it is particularly feasible for Cartesian sampling schemes. In 2D Fourier imaging with common Cartesian sampling of k-space sensitivity encoding by means of a receiver array enables to reduce the number of Fourier encoding steps.
SENSE reconstruction without artifacts relies on accurate knowledge of the individual coil sensitivities. For sensitivity assessment, low-resolution, fully Fourier-encoded reference images are required, obtained with each array element and with a body coil.
The major negative point of parallel imaging techniques is that they diminish SNR in proportion to the numbers of reduction factors. R is the factor by which the number of k-space samples is reduced. In standard Fourier imaging reducing the sampling density results in the reduction of the FOV, causing aliasing. In fact, SENSE reconstruction in the Cartesian case is efficiently performed by first creating one such aliased image for each array element using discrete Fourier transformation (DFT).
The next step then is to create a full-FOV image from the set of intermediate images. To achieve this one must undo the signal superposition underlying the fold-over effect. That is, for each pixel in the reduced FOV the signal contributions from a number of positions in the full FOV need to be separated. These positions form a Cartesian grid corresponding to the size of the reduced FOV.
The advantages are especially true for contrast-enhanced MR imaging such as dynamic liver MRI (liver imaging) , 3 dimensional magnetic resonance angiography (3D MRA), and magnetic resonance cholangiopancreaticography (MRCP).
The excellent scan speed of SENSE allows for acquisition of two separate sets of hepatic MR images within the time regarded as the hepatic arterial-phase (double arterial-phase technique) as well as that of multidetector CT.
SENSE can also increase the time efficiency of spatial signal encoding in 3D MRA. With SENSE, even ultrafast (sub second) 4D MRA can be realized.
For MRCP acquisition, high-resolution 3D MRCP images can be constantly provided by SENSE. This is because SENSE resolves the presence of the severe motion artifacts due to longer acquisition time. Longer acquisition time, which results in diminishing image quality, is the greatest problem for 3D MRCP imaging.
In addition, SENSE reduces the train of gradient echoes in combination with a faster k-space traversal per unit time, thereby dramatically improving the image quality of single shot echo planar imaging (i.e. T2 weighted, diffusion weighted imaging).

(SNR or S/N) The signal to noise ratio is used in MRI to describe the relative contributions to a detected signal of the true signal and random superimposed signals ('background noise') - a criterion for image quality.
One common method to increase the SNR is to average several measurements of the signal, on the expectation that random contributions will tend to cancel out. The SNR can also be improved by sampling larger volumes (increasing the field of view and slice thickness with a corresponding loss of spatial resolution) or, within limits, by increasing the strength of the magnetic field used. Surface coils can also be used to improve local signal intensity. The SNR will depend, in part, on the electrical properties of the sample or patient being studied. The SNR increases in proportion to voxel volume (1/resolution), the square root of the number of acquisitions (NEX), and the square root of the number of scans (phase encodings). SNR decreases with the field of view squared (FOV2) and wider bandwidths. See also Signal Intensity and Spin Density.

Measuring SNR:
Record the mean value of a small ROI placed in the most homogeneous area of tissue with high signal intensity (e.g. white matter in thalamus). Calculate the standard deviation for the largest possible ROI placed outside the object in the image background (avoid ghosting/aliasing or eye movement artifact regions).
The SNR is then:
Mean Signal/Standard Deviation of Background Noise

Undersampling is the decrease in data to increase image acquisition speed (shorter scan times without loss of quality - increased productivity - reduced cost of equipment). There are different strategies to decrease data without losing quality (e.g. reduction of the FOV in one or more spatial directions - RFOV).
Reduction in data normally is associated with an increase in aliasing (degradation of the SNR through backfolding of the entire noise spectrum), or with other artifact caused by missing data, which results in fine lines.