Literature DB >> 17354645

A review of methods for correction of intensity inhomogeneity in MRI.

Uros Vovk1, Franjo Pernus, Bostjan Likar.   

Abstract

Medical image acquisition devices provide a vast amount of anatomical and functional information, which facilitate and improve diagnosis and patient treatment, especially when supported by modern quantitative image analysis methods. However, modality specific image artifacts, such as the phenomena of intensity inhomogeneity in magnetic resonance images (MRI), are still prominent and can adversely affect quantitative image analysis. In this paper, numerous methods that have been developed to reduce or eliminate intensity inhomogeneities in MRI are reviewed. First, the methods are classified according to the inhomogeneity correction strategy. Next, different qualitative and quantitative evaluation approaches are reviewed. Third, 60 relevant publications are categorized according to several features and analyzed so as to reveal major trends, popularity, evaluation strategies and applications. Finally, key evaluation issues and future development of the inhomogeneity correction field, supported by the results of the analysis, are discussed.

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Mesh:

Year:  2007        PMID: 17354645     DOI: 10.1109/TMI.2006.891486

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  115 in total

1.  Bias field inconsistency correction of motion-scattered multislice MRI for improved 3D image reconstruction.

Authors:  Kio Kim; Piotr A Habas; Vidya Rajagopalan; Julia A Scott; James M Corbett-Detig; Francois Rousseau; A James Barkovich; Orit A Glenn; Colin Studholme
Journal:  IEEE Trans Med Imaging       Date:  2011-04-19       Impact factor: 10.048

2.  Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

Authors:  Yuanjie Zheng; Murray Grossman; Suyash P Awate; James C Gee
Journal:  Med Image Comput Comput Assist Interv       Date:  2009

Review 3.  Computational analysis of cerebral cortex.

Authors:  Hidemasa Takao; Osamu Abe; Kuni Ohtomo
Journal:  Neuroradiology       Date:  2010-05-18       Impact factor: 2.804

4.  Evaluation of image quality of a 32-channel versus a 12-channel head coil at 1.5T for MR imaging of the brain.

Authors:  P T Parikh; G S Sandhu; K A Blackham; M D Coffey; D Hsu; K Liu; J Jesberger; M Griswold; J L Sunshine
Journal:  AJNR Am J Neuroradiol       Date:  2010-12-16       Impact factor: 3.825

5.  Influence of signal intensity non-uniformity on brain volumetry using an atlas-based method.

Authors:  Masami Goto; Osamu Abe; Tosiaki Miyati; Hiroyuki Kabasawa; Hidemasa Takao; Naoto Hayashi; Tomomi Kurosu; Takeshi Iwatsubo; Fumio Yamashita; Hiroshi Matsuda; Harushi Mori; Akira Kunimatsu; Shigeki Aoki; Kenji Ino; Keiichi Yano; Kuni Ohtomo
Journal:  Korean J Radiol       Date:  2012-06-18       Impact factor: 3.500

Review 6.  Principles and methods for automatic and semi-automatic tissue segmentation in MRI data.

Authors:  Lei Wang; Teodora Chitiboi; Hans Meine; Matthias Günther; Horst K Hahn
Journal:  MAGMA       Date:  2016-01-11       Impact factor: 2.310

7.  Fast algorithm for calculation of inhomogeneity gradient in magnetic resonance imaging data.

Authors:  Cheukkai Hui; Yu Xiang Zhou; Ponnada Narayana
Journal:  J Magn Reson Imaging       Date:  2010-11       Impact factor: 4.813

8.  Intensity non-uniformity correction using N3 on 3-T scanners with multichannel phased array coils.

Authors:  Richard G Boyes; Jeff L Gunter; Chris Frost; Andrew L Janke; Thomas Yeatman; Derek L G Hill; Matt A Bernstein; Paul M Thompson; Michael W Weiner; Norbert Schuff; Gene E Alexander; Ronald J Killiany; Charles DeCarli; Clifford R Jack; Nick C Fox
Journal:  Neuroimage       Date:  2007-10-30       Impact factor: 6.556

9.  Restoration of MRI data for intensity non-uniformities using local high order intensity statistics.

Authors:  Stathis Hadjidemetriou; Colin Studholme; Susanne Mueller; Michael Weiner; Norbert Schuff
Journal:  Med Image Anal       Date:  2008-06-07       Impact factor: 8.545

10.  Automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI using an atlas-aided fuzzy C-means method.

Authors:  Shandong Wu; Susan P Weinstein; Emily F Conant; Despina Kontos
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

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