Intensity non-uniformity correction in MRI: existing methods and their validation
- PMID: 16307900
- DOI: 10.1016/j.media.2005.09.004
Intensity non-uniformity correction in MRI: existing methods and their validation
Abstract
Magnetic resonance imaging is a popular and powerful non-invasive imaging technique. Automated analysis has become mandatory to efficiently cope with the large amount of data generated using this modality. However, several artifacts, such as intensity non-uniformity, can degrade the quality of acquired data. Intensity non-uniformity consists in anatomically irrelevant intensity variation throughout data. It can be induced by the choice of the radio-frequency coil, the acquisition pulse sequence and by the nature and geometry of the sample itself. Numerous methods have been proposed to correct this artifact. In this paper, we propose an overview of existing methods. We first sort them according to their location in the acquisition/processing pipeline. Sorting is then refined based on the assumptions those methods rely on. Next, we present the validation protocols used to evaluate these different correction schemes both from a qualitative and a quantitative point of view. Finally, availability and usability of the presented methods is discussed.
Similar articles
-
Interplay between intensity standardization and inhomogeneity correction in MR image processing.IEEE Trans Med Imaging. 2005 May;24(5):561-76. doi: 10.1109/TMI.2004.843256. IEEE Trans Med Imaging. 2005. PMID: 15889544
-
Voxel-based iterative sensitivity (VBIS) analysis: methods and a validation of intensity scaling for T2-weighted imaging of hippocampal sclerosis.Neuroimage. 2009 Feb 1;44(3):812-9. doi: 10.1016/j.neuroimage.2008.09.055. Epub 2008 Oct 19. Neuroimage. 2009. PMID: 18996207
-
Method to correct intensity inhomogeneity in MR images for atherosclerosis characterization.IEEE Trans Med Imaging. 2006 May;25(5):539-52. doi: 10.1109/TMI.2006.871418. IEEE Trans Med Imaging. 2006. PMID: 16689259
-
A review of methods for correction of intensity inhomogeneity in MRI.IEEE Trans Med Imaging. 2007 Mar;26(3):405-21. doi: 10.1109/TMI.2006.891486. IEEE Trans Med Imaging. 2007. PMID: 17354645 Review.
-
Magnetic resonance imaging and the reduction of motion artifacts: review of the principles.Technol Health Care. 1997 Dec;5(6):419-35. Technol Health Care. 1997. PMID: 9696161 Review.
Cited by
-
Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features.Int J Comput Assist Radiol Surg. 2014 Mar;9(2):241-53. doi: 10.1007/s11548-013-0922-7. Epub 2013 Jul 17. Int J Comput Assist Radiol Surg. 2014. PMID: 23860630
-
Tissue Border Enhancement by inversion recovery MRI at 7.0 Tesla.Neuroradiology. 2014 Jul;56(7):517-23. doi: 10.1007/s00234-014-1365-8. Epub 2014 Apr 25. Neuroradiology. 2014. PMID: 24763967
-
Multiple-profile homogeneous image combination: application to phase-cycled SSFP and multicoil imaging.Magn Reson Med. 2008 Sep;60(3):732-8. doi: 10.1002/mrm.21720. Magn Reson Med. 2008. PMID: 18727089 Free PMC article.
-
Improving MR image quality with a multi-task model, using convolutional losses.BMC Med Imaging. 2023 Oct 2;23(1):148. doi: 10.1186/s12880-023-01109-z. BMC Med Imaging. 2023. PMID: 37784039 Free PMC article.
-
Future Brain and Spinal Cord Volumetric Imaging in the Clinic for Monitoring Treatment Response in MS.Curr Treat Options Neurol. 2018 Apr 20;20(6):17. doi: 10.1007/s11940-018-0504-7. Curr Treat Options Neurol. 2018. PMID: 29679165 Review.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical