title: Intensity Inhomogeneity Correction of Magnetic Resonance Images using Patches.
abstract: This paper presents a patch-based non-parametric approach to the correction of intensity inhomogeneity from magnetic resonance (MR) images of the human brain. During image acquisition, the inhomogeneity present in the radio-frequency coil, is usually manifested on the reconstructed MR image as a smooth shading effect. This artifact can significantly deteriorate the performance of any kind of image processing algorithm that uses intensities as a feature. Most of the current inhomogeneity correction techniques use explicit smoothness assumptions on the inhomogeneity field, which sometimes limit their performance if the actual inhomogeneity is not smooth, a problem that becomes prevalent in high fields. The proposed patch-based inhomogeneity correction method does not assume any parametric smoothness model, instead, it uses patches from an atlas of an inhomogeneity-free image to do the correction. Preliminary results show that the proposed method is comparable to N3, a current state of the art method, when the inhomogeneity is smooth, and outperforms N3 when the inhomogeneity contains non-smooth elements.
authors: Image Analysis and Communications Laboratory, Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA.
authors: Snehashis
authors: S
authors: Roy
authors: Image Analysis and Communications Laboratory, Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA.
authors: Aaron
authors: A
authors: Carass
authors: MeDIC, Neurology Division, Radiology and Radiological Science, The Johns Hopkins University, Baltimore, MD, USA.
authors: Pierre-Louis
authors: PL
authors: Bazin
authors: Image Analysis and Communications Laboratory, Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA.
authors: Jerry L
authors: JL
authors: Prince
keywords: MRI; RF field inhomogeneity; artifact correction; bias field; gain field; intensity inhomogeneity; non-uniformity; patch; segmentation