Literature DB >> 9469718

Correction for variations in MRI scanner sensitivity in brain studies with histogram matching.

L Wang1, H M Lai, G J Barker, D H Miller, P S Tofts.   

Abstract

Quantitative comparisons of abnormalities in MRI scans between patients or within patients serially are affected by variations in MR scanner performance. A histogram matching method is proposed to correct for variation in scanner sensitivity. It is demonstrated that this histogram matching method reduced the variation in white matter intensities across normal subjects from 7.5 to 2.5% and provided a method to remove the threshold dependency in lesion volume measurement with global thresholding in patients with multiple sclerosis (MS). The effectiveness of the method was compared with three other possible correction schemes. The histogram matching method was shown to be 2 to 5 times better.

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Year:  1998        PMID: 9469718     DOI: 10.1002/mrm.1910390222

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  14 in total

1.  Accurate template-based correction of brain MRI intensity distortion with application to dementia and aging.

Authors:  C Studholme; V Cardenas; E Song; F Ezekiel; A Maudsley; M Weiner
Journal:  IEEE Trans Med Imaging       Date:  2004-01       Impact factor: 10.048

2.  Magnetic Resonance Image Example-Based Contrast Synthesis.

Authors:  Snehashis Roy; Aaron Carass; Jerry L Prince
Journal:  IEEE Trans Med Imaging       Date:  2013-09-16       Impact factor: 10.048

3.  Pulse Sequence based Multi-acquisition MR Intensity Normalization.

Authors:  Amod Jog; Snehashis Roy; Aaron Carass; Jerry L Prince
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-03

Review 4.  Segmentation of multiple sclerosis lesions in MR images: a review.

Authors:  Daryoush Mortazavi; Abbas Z Kouzani; Hamid Soltanian-Zadeh
Journal:  Neuroradiology       Date:  2011-05-17       Impact factor: 2.804

5.  Tissue-based MRI intensity standardization: application to multicentric datasets.

Authors:  Nicolas Robitaille; Abderazzak Mouiha; Burt Crépeault; Fernando Valdivia; Simon Duchesne
Journal:  Int J Biomed Imaging       Date:  2012-05-03

6.  Retrospective illumination correction of retinal images.

Authors:  Libor Kubecka; Jiri Jan; Radim Kolar
Journal:  Int J Biomed Imaging       Date:  2010-07-04

7.  An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features.

Authors:  Muwei Li; Kenichi Oishi; Xiaohai He; Yuanyuan Qin; Fei Gao; Susumu Mori
Journal:  PLoS One       Date:  2014-08-20       Impact factor: 3.240

8.  Statistical normalization techniques for magnetic resonance imaging.

Authors:  Russell T Shinohara; Elizabeth M Sweeney; Jeff Goldsmith; Navid Shiee; Farrah J Mateen; Peter A Calabresi; Samson Jarso; Dzung L Pham; Daniel S Reich; Ciprian M Crainiceanu
Journal:  Neuroimage Clin       Date:  2014-08-15       Impact factor: 4.881

9.  Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

Authors:  Xiaofei Sun; Lin Shi; Yishan Luo; Wei Yang; Hongpeng Li; Peipeng Liang; Kuncheng Li; Vincent C T Mok; Winnie C W Chu; Defeng Wang
Journal:  Biomed Eng Online       Date:  2015-07-28       Impact factor: 2.819

Review 10.  Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis.

Authors:  H Vrenken; M Jenkinson; M A Horsfield; M Battaglini; R A van Schijndel; E Rostrup; J J G Geurts; E Fisher; A Zijdenbos; J Ashburner; D H Miller; M Filippi; F Fazekas; M Rovaris; A Rovira; F Barkhof; N de Stefano
Journal:  J Neurol       Date:  2012-12-21       Impact factor: 4.849

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