(FOV) Defined as the size of the two or three dimensional spatial encoding area of the image. Usually defined in units of mm². The FOV is the square image area that contains the object of interest to be measured. The smaller the FOV, the higher the resolution and the smaller the voxel size but the lower the measured signal. Useful for decreasing the scantime is a field of view different in the frequency and phase encoding directions (rectangular field of view - RFOV).
The magnetic field homogeneity decreases as more tissue is imaged (greater FOV). As a result the precessional frequencies change across the imaging volume. That can be a problem for fat suppression imaging. This fat is precessing at the expected frequency only in the center of the imaging volume. E.g. frequency specific fat saturation pulses become less effective when the field of view is increased. It is best to use smaller field of views when applying fat saturation pulses.

Smaller FOV required higher gradient strength and concludes low signal. Therefore you have to find a compromise between these factors. The right choice of the field of view is important for MR image quality. When utilizing small field of views and scanning at a distance from the isocenter (more problems with artifacts) it is obviously important to ensure that the region of interest is within the scanning volume.
A smaller FOV in one direction is available with the function rectangular field of view (RFOV).

See also Field Inhomogeneity Artifact.

The image resolution is the level of detail of an image and a measurement of image quality. Higher resolution means more image detail, for example when two structures 1 mm apart are distinguishable in an image, this picture has a higher resolution than an image where they are not to distinguish.
More data points in an MR image (with same FOV) will decrease the pixel size, but not accurately improve the resolution because the different MRI sequences influence the contrast and the discernment of different tissues. With high contrast and optimal signal to noise ratio, the image resolution is depend on FOV and number of data points of a picture, but T2* effects have an additional influence.

A signal to noise improvement method that is accomplished by taking the average of several FID`s made under similar conditions to suppress the effects of random variations or random artifacts. It is a common method to increase the SNR by averaging several measurements of the signal.
The number of averages is also referred to as the number of excitations (NEX) or the number of acquisitions (NSA). Doubling the number of acquisitions will increase the SNR by √2. The approximate amount of improvement in signal to noise (SNR) ratio is calculated as the square root of the number of excitations.
By using multiple averages, respiratory motion can be reduced in the same way that multiple averages increase the signal to noise ratio. NEX/NSA will increase SNR but will not affect contrast unless the tissues are being lost in noise (low CNR). Scan time scales directly with NEX/NSA and SNR as the square root of NEX/NSA.
The use of phase array coils allows the number of signal averages to be decreased with their superior SNR and resolution, thereby decreasing scan time.

(THK) The thickness of an imaging slice. As the slice profile may not be sharp edged, a criterion such as the distance between the points at half the sensitivity of the maximum (FWHM) or the equivalent rectangular width (the width of a rectangular slice profile with the same maximum height and same area) is used to determine thickness.

For the image quality its important to choose the best fitting slice thickness for an examination. When a small item is entirely contained within the slice thickness with other tissue of differing signal intensity then the resulting signal displayed on the image is a combination of these two intensities. If the slice is the same thickness or thinner than the small structure, only that structures signal intensity is displayed on the image. This partial volume averaging effect explains the vanishing of fine details by choosing slices too large for the scanned object.

See also Partial Volume Artifact.