Correction of intensity inhomogeneity in magnetic resonance imaging

摘要

Intensity inhomogeneities are very common in MR images, especially at higher field strengths. This can cause problems for image interpretation, as well as introduce errors in many quantitative post-processing methods. Here it is proposed to use a Generative Adversarial Network that is trained to provide homogeneous MR images of a particular anatomy. During application, the network is used to produce the (homogeneous) image most similar to the query image (QI). A conventional fitting method can then be used to identify the inhomogeneity field and correct the query image. Figure 1