Gradient Moment Nulling (GMN) is a technique used in magnetic resonance imaging (MRI) to reduce artifacts caused by magnetic field inhomogeneities. In MRI, the magnetic field needs to be uniform to obtain high-quality images. However, in reality, the magnetic field can be distorted due to various factors such as imperfections in the scanner's hardware or the presence of external objects. To understand GMN, need understand the concept of the gradient moment. In MRI, gradients are used to encode spatial information into the acquired data. Gradients are magnetic fields that vary linearly with position, allowing us to determine the location of signals within the body. The gradient moment is a measure of the area under the gradient field curve over time. It represents the spatial encoding ability of the gradient field. When the gradient moments are not properly nullified, they can cause image artifacts, such as blurring, distortion, or signal loss. GMN aims to eliminate these artifacts by adjusting the gradient moments during the MRI sequence. By nulling the gradient moments, GMN helps improve the image quality in MRI by reducing artifacts caused by magnetic field inhomogeneities. This technique is particularly useful in high-field MRI systems where magnetic field distortions are more pronounced. To summarize, Gradient Moment Nulling (GMN) is a technique used in MRI to minimize artifacts caused by magnetic field inhomogeneities. It involves analyzing the gradient moments, calibrating the system, calculating correction values, applying these values during the MRI sequence, and iteratively optimizing the gradient moments. GMN helps improve image quality by reducing artifacts and ensuring a more uniform magnetic field.
*(im not a kind of expert just someone who read and do a lot of notes)