Literature DB >> 23165035

A Review on MR Image Intensity Inhomogeneity Correction.

Zujun Hou1.   

Abstract

Intensity inhomogeneity (IIH) is often encountered in MR imaging, and a number of techniques have been devised to correct this artifact. This paper attempts to review some of the recent developments in the mathematical modeling of IIH field. Low-frequency models are widely used, but they tend to corrupt the low-frequency components of the tissue. Hypersurface models and statistical models can be adaptive to the image and generally more stable, but they are also generally more complex and consume more computer memory and CPU time. They are often formulated together with image segmentation within one framework and the overall performance is highly dependent on the segmentation process. Beside these three popular models, this paper also summarizes other techniques based on different principles. In addition, the issue of quantitative evaluation and comparative study are discussed.

Year:  2006        PMID: 23165035      PMCID: PMC2324029          DOI: 10.1155/IJBI/2006/49515

Source DB:  PubMed          Journal:  Int J Biomed Imaging        ISSN: 1687-4188


  20 in total

1.  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

Review 2.  Baby brain atlases.

Authors:  Kenichi Oishi; Linda Chang; Hao Huang
Journal:  Neuroimage       Date:  2018-04-03       Impact factor: 6.556

3.  A computerized MRI biomarker quantification scheme for a canine model of Duchenne muscular dystrophy.

Authors:  Jiahui Wang; Zheng Fan; Krista Vandenborne; Glenn Walter; Yael Shiloh-Malawsky; Hongyu An; Joe N Kornegay; Martin A Styner
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-01-09       Impact factor: 2.924

4.  Intensity Inhomogeneity Correction of Magnetic Resonance Images using Patches.

Authors:  Snehashis Roy; Aaron Carass; Pierre-Louis Bazin; Jerry L Prince
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2011-03-11

5.  A hybrid method based on fuzzy clustering and local region-based level set for segmentation of inhomogeneous medical images.

Authors:  Maryam Rastgarpour; Jamshid Shanbehzadeh; Hamid Soltanian-Zadeh
Journal:  J Med Syst       Date:  2014-06-24       Impact factor: 4.460

6.  A deep learning framework for efficient analysis of breast volume and fibroglandular tissue using MR data with strong artifacts.

Authors:  Tatyana Ivanovska; Thomas G Jentschke; Amro Daboul; Katrin Hegenscheid; Henry Völzke; Florentin Wörgötter
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-03-06       Impact factor: 2.924

7.  A subspace-based coil combination method for phased-array magnetic resonance imaging.

Authors:  Derya Gol Gungor; Lee C Potter
Journal:  Magn Reson Med       Date:  2015-03-13       Impact factor: 4.668

8.  Minimization of region-scalable fitting energy for image segmentation.

Authors:  Chunming Li; Chiu-Yen Kao; John C Gore; Zhaohua Ding
Journal:  IEEE Trans Image Process       Date:  2008-10       Impact factor: 10.856

Review 9.  Segmentation and quantification of adipose tissue by magnetic resonance imaging.

Authors:  Houchun Harry Hu; Jun Chen; Wei Shen
Journal:  MAGMA       Date:  2015-09-04       Impact factor: 2.310

10.  Intensity non-uniformity correction in MR imaging using residual cycle generative adversarial network.

Authors:  Xianjin Dai; Yang Lei; Yingzi Liu; Tonghe Wang; Lei Ren; Walter J Curran; Pretesh Patel; Tian Liu; Xiaofeng Yang
Journal:  Phys Med Biol       Date:  2020-11-27       Impact factor: 3.609

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