Quick Overview
Please note that there are different common names for this MRI artifact.

The Gibbs or ringing artifact appears as a series of lines in the MR image parallel to abrupt and intense changes in the object at this location. This artifact does not occur visibly on smooth objects. This artifact is caused by the Gibbs phenomenon, an overshoot or ringing of Fourier series occurring at discontinuities.
In the spinal cord, a small syrinx can be simulated by the Gibbs phenomenon. Gibbs artifacts are also seen in other regions, for example the brain//skull interface.
Fine lines visible in an image may be due to undersampling of the high spatial frequencies, respectively incomplete digitization of the echo.
With more encoding steps the Gibbs artifacts is less intense and narrower. Therefore, e.g. the artifact is more intense in the 256 point dimension of a 256x512 acquisition matrix.

This problem can only be resolved by smoothing filters (LanczosSigmaFactor, 2-D Exponential Filtering, Gegenbauer Reconstruction etc.) or with a higher acquisition matrix and/or a smaller FOV, to smooth the object.

See also Gibbs Phenomenon and Apodization.

If the receiving RF coil is sensitive to tissue signal arising from outside the desired FOV, this undesired signal may be incorrectly mapped to a location within the image, a phenomenon known as aliasing. This is a consequence of the acquired k-space frequencies not being sampled densely enough, whereby portions of the object outside of the desired FOV get mapped to an incorrect location inside the FOV. The sampling frequency should be at least twice the frequency being sampled. The maximum measurable frequency is therefore equal to half the sampling frequency. This is the so-called Nyquist limit. When the frequency is higher than the Nyquist limit, aliasing occurs.
A similar problem occurs in the phase encoding direction, where the phases of signal-bearing tissues outside of the FOV in the y-direction are a replication of the phases that are encoded within the FOV. This signal will be mapped, or wrapped back into the image at incorrect locations, and is seen as artifact.

See also Aliasing Artifact.

Quick Overview
Please note that there are different common names for this artifact.

During frequency encoding, fat protons precess slower than water protons in the same slice because of their magnetic shielding. Through the difference in resonance frequency between water and fat, protons at the same location are misregistrated (dislocated) by the Fourier transformation, when converting MRI signals from frequency to spatial domain. This chemical shift misregistration cause accentuation of any fat-water interfaces along the frequency axis and may be mistaken for pathology. Where fat and water are in the same location, this artifact can be seen as a bright or dark band at the edge of the anatomy.
Protons in fat and water molecules are separated by a chemical shift of about 3.5 ppm. The actual shift in Hertz (Hz) depends on the magnetic field strength of the magnet being used. Higher field strength increases the misregistration, while in contrast a higher gradient strength has a positive effect. For a 0.3 T system operating at 12.8 MHz the shift will be 44.8 Hz compared with a 223.6 Hz shift for a 1.5 T system operating at 63.9 MHz.

For artifact reduction helps a smaller water fat shift (higher bandwidth), a higher matrix, an in phase TE or a spin echo technique. Since the misregistration offset is present in the read out axis the patient may be rescanned with this axis parallel to the fat-water interface. Steeper gradient may be employed to reduce the chemical shift offset in mm. Another strategy is to employ specialized pulse sequences such as fat saturation or inversion recovery imaging. Fat suppression techniques eliminate chemical shift artifacts caused by the lack of fat signal.

See also Black Boundary Artifact and Magnetic Resonance Spectroscopy.

Magnetic resonance imaging (MRI) is based on the magnetic resonance phenomenon, and is used for medical diagnostic imaging since ca. 1977 (see also MRI History).
The first developed MRI devices were constructed as long narrow tunnels. In the meantime the magnets became shorter and wider. In addition to this short bore magnet design, open MRI machines were created. MRI machines with open design have commonly either horizontal or vertical opposite installed magnets and obtain more space and air around the patient during the MRI test.
The basic hardware components of all MRI systems are the magnet, producing a stable and very intense magnetic field, the gradient coils, creating a variable field and radio frequency (RF) coils which are used to transmit energy and to encode spatial positioning. A computer controls the MRI scanning operation and processes the information.
The range of used field strengths for medical imaging is from 0.15 to 3 T. The open MRI magnets have usually field strength in the range 0.2 Tesla to 0.35 Tesla. The higher field MRI devices are commonly solenoid with short bore superconducting magnets, which provide homogeneous fields of high stability.
There are this different types of magnets:
The majority of superconductive magnets are based on niobium-titanium (NbTi) alloys, which are very reliable and require extremely uniform fields and extreme stability over time, but require a liquid helium cryogenic system to keep the conductors at approximately 4.2 Kelvin (-268.8° Celsius). To maintain this temperature the magnet is enclosed and cooled by a cryogen containing liquid helium (sometimes also nitrogen).
The gradient coils are required to produce a linear variation in field along one direction, and to have high efficiency, low inductance and low resistance, in order to minimize the current requirements and heat deposition. A Maxwell coil usually produces linear variation in field along the z-axis; in the other two axes it is best done using a saddle coil, such as the Golay coil.
The radio frequency coils used to excite the nuclei fall into two main categories; surface coils and volume coils. The essential element for spatial encoding, the gradient coil sub-system of the MRI scanner is responsible for the encoding of specialized contrast such as flow information, diffusion information, and modulation of magnetization for spatial tagging.
An analog to digital converter turns the nuclear magnetic resonance signal to a digital signal. The digital signal is then sent to an image processor for Fourier transformation and the image of the MRI scan is displayed on a monitor.

For Ultrasound Imaging (USI) see Ultrasound Machine at Medical-Ultrasound-Imaging.com.

See also the related poll results: 'In 2010 your scanner will probably work with a field strength of' and 'Most outages of your scanning system are caused by failure of'

Quick Overview
Please note that there are different common names for this artifact.

Machine imperfection-based artifacts manifest themselves due to the fact that the odd k-space lines are acquired in a different direction than the even k-space lines. Slight differences in timing result in shifts of the echo in the acquisition window. By the shift theorem, such shifts in the time domain data then produce linear phase differences in the frequency domain data.
Without correction, such phase differences in every second line produce striped ghosts with a shift of half the field of view, so-called Nyquist ghosts. Shifts in the applied magnetic field can also produce similar (but constant in amplitude) ghosts.
This artifact is commonly seen in an EPI image and can arise from both, hardware and sample imperfections.
A further source of machine-based artifact arises from the need to acquire the signal as quickly as possible. For this reason the EPI signal is often acquired during times when the gradients are being switched. Such sampling effectively means that the k-space sampling is not uniform, resulting in ringing artifacts in the image.

Such artifacts can be minimized by careful setup of the spectrometer and/or correction of the data. For this reasons reference data are often collected, either as a separate scan or embedded in the imaging data. The non-uniform sampling can be removed by knowing the form of the gradient switching. It is possible to regrid the data onto a uniform k-space grid.