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Items: 1 to 20 of 113

1.

Automated determination of brain parenchymal fraction in multiple sclerosis.

Vågberg M, Lindqvist T, Ambarki K, Warntjes JB, Sundström P, Birgander R, Svenningsson A.

AJNR Am J Neuroradiol. 2013 Mar;34(3):498-504. doi: 10.3174/ajnr.A3262.

2.

Disease modeling in multiple sclerosis: assessment and quantification of sources of variability in brain parenchymal fraction measurements.

Sampat MP, Healy BC, Meier DS, Dell'Oglio E, Liguori M, Guttmann CR.

Neuroimage. 2010 Oct 1;52(4):1367-73. doi: 10.1016/j.neuroimage.2010.03.075.

PMID:
20362675
3.

Reliability of longitudinal brain volume loss measurements between 2 sites in patients with multiple sclerosis: comparison of 7 quantification techniques.

Durand-Dubief F, Belaroussi B, Armspach JP, Dufour M, Roggerone S, Vukusic S, Hannoun S, Sappey-Marinier D, Confavreux C, Cotton F.

AJNR Am J Neuroradiol. 2012 Nov;33(10):1918-24. doi: 10.3174/ajnr.A3107.

4.

Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors.

Dell'Oglio E, Ceccarelli A, Glanz BI, Healy BC, Tauhid S, Arora A, Saravanan N, Bruha MJ, Vartanian AV, Dupuy SL, Benedict RH, Bakshi R, Neema M.

J Neuroimaging. 2015 Mar-Apr;25(2):191-9. doi: 10.1111/jon.12194.

5.

A semiautomated measure of whole-brain atrophy in multiple sclerosis.

Bermel RA, Sharma J, Tjoa CW, Puli SR, Bakshi R.

J Neurol Sci. 2003 Apr 15;208(1-2):57-65.

PMID:
12639726
6.

Comparison of three different methods for measurement of cervical cord atrophy in multiple sclerosis.

Zivadinov R, Banas AC, Yella V, Abdelrahman N, Weinstock-Guttman B, Dwyer MG.

AJNR Am J Neuroradiol. 2008 Feb;29(2):319-25.

7.

Evaluation of automated techniques for the quantification of grey matter atrophy in patients with multiple sclerosis.

Derakhshan M, Caramanos Z, Giacomini PS, Narayanan S, Maranzano J, Francis SJ, Arnold DL, Collins DL.

Neuroimage. 2010 Oct 1;52(4):1261-7. doi: 10.1016/j.neuroimage.2010.05.029.

PMID:
20483380
8.

Quantitative diffusion weighted imaging measures in patients with multiple sclerosis.

Tavazzi E, Dwyer MG, Weinstock-Guttman B, Lema J, Bastianello S, Bergamaschi R, Cosi V, Benedict RH, Munschauer FE 3rd, Zivadinov R.

Neuroimage. 2007 Jul 1;36(3):746-54.

PMID:
17498974
9.

Medulla oblongata volume: a biomarker of spinal cord damage and disability in multiple sclerosis.

Liptak Z, Berger AM, Sampat MP, Charil A, Felsovalyi O, Healy BC, Hildenbrand P, Khoury SJ, Weiner HL, Bakshi R, Guttmann CR.

AJNR Am J Neuroradiol. 2008 Sep;29(8):1465-70. doi: 10.3174/ajnr.A1162.

10.

Whole-brain atrophy in multiple sclerosis measured by automated versus semiautomated MR imaging segmentation.

Sharma J, Sanfilipo MP, Benedict RH, Weinstock-Guttman B, Munschauer FE 3rd, Bakshi R.

AJNR Am J Neuroradiol. 2004 Jun-Jul;25(6):985-96.

11.

Multiple sclerosis lesion segmentation using an automatic multimodal graph cuts.

García-Lorenzo D, Lecoeur J, Arnold DL, Collins DL, Barillot C.

Med Image Comput Comput Assist Interv. 2009;12(Pt 2):584-91.

PMID:
20426159
12.

Measurement of brain atrophy in subcortical vascular disease: a comparison of different approaches and the impact of ischaemic lesions.

O'Sullivan M, Jouvent E, Saemann PG, Mangin JF, Viswanathan A, Gschwendtner A, Bracoud L, Pachai C, Chabriat H, Dichgans M.

Neuroimage. 2008 Nov 1;43(2):312-20. doi: 10.1016/j.neuroimage.2008.07.049.

PMID:
18722537
13.

Effects of gadolinium contrast agent administration on automatic brain tissue classification of patients with multiple sclerosis.

Warntjes JB, Tisell A, Landtblom AM, Lundberg P.

AJNR Am J Neuroradiol. 2014 Jul;35(7):1330-6. doi: 10.3174/ajnr.A3890.

14.

In vivo quantitative evaluation of brain tissue damage in multiple sclerosis using gradient echo plural contrast imaging technique.

Sati P, Cross AH, Luo J, Hildebolt CF, Yablonskiy DA.

Neuroimage. 2010 Jul 1;51(3):1089-97. doi: 10.1016/j.neuroimage.2010.03.045.

15.

Segmentation of brain magnetic resonance images for measurement of gray matter atrophy in multiple sclerosis patients.

Nakamura K, Fisher E.

Neuroimage. 2009 Feb 1;44(3):769-76. doi: 10.1016/j.neuroimage.2008.09.059.

16.

Subcortical gray matter segmentation and voxel-based analysis using transverse relaxation and quantitative susceptibility mapping with application to multiple sclerosis.

Cobzas D, Sun H, Walsh AJ, Lebel RM, Blevins G, Wilman AH.

J Magn Reson Imaging. 2015 Dec;42(6):1601-10. doi: 10.1002/jmri.24951.

PMID:
25980643
17.

Short-term brain atrophy changes in relapsing-remitting multiple sclerosis.

Zivadinov R, Bagnato F, Nasuelli D, Bastianello S, Bratina A, Locatelli L, Watts K, Finamore L, Grop A, Dwyer M, Catalan M, Clemenzi A, Millefiorini E, Bakshi R, Zorzon M.

J Neurol Sci. 2004 Aug 30;223(2):185-93.

PMID:
15337621
18.

Reproducibility and accuracy of quantitative magnetic resonance imaging techniques of whole-brain atrophy measurement in multiple sclerosis.

Zivadinov R, Grop A, Sharma J, Bratina A, Tjoa CW, Dwyer M, Zorzon M.

J Neuroimaging. 2005 Jan;15(1):27-36.

PMID:
15574571
19.

Multiple sclerosis: hyperintense lesions in the brain on T1-weighted MR images assessed by diffusion tensor imaging.

Zhou F, Shiroishi M, Gong H, Zee CS.

J Magn Reson Imaging. 2010 Apr;31(4):789-95. doi: 10.1002/jmri.22103.

PMID:
20373421
20.

Brain parenchymal fraction in an age-stratified healthy population - determined by MRI using manual segmentation and three automated segmentation methods.

Vågberg M, Ambarki K, Lindqvist T, Birgander R, Svenningsson A.

J Neuroradiol. 2016 Dec;43(6):384-391. doi: 10.1016/j.neurad.2016.08.002.

PMID:
27720265
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