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Items: 13

1.

Developmental Hip Dysplasia Diagnosis at Three-dimensional US: A Multicenter Study.

Zonoobi D, Hareendranathan A, Mostofi E, Mabee M, Pasha S, Cobzas D, Rao P, Dulai SK, Kapur J, Jaremko JL.

Radiology. 2018 Jun;287(3):1003-1015. doi: 10.1148/radiol.2018172592. Epub 2018 Apr 24.

PMID:
29688160
2.

Discriminative analysis of regional evolution of iron and myelin/calcium in deep gray matter of multiple sclerosis and healthy subjects.

Elkady AM, Cobzas D, Sun H, Blevins G, Wilman AH.

J Magn Reson Imaging. 2018 Mar 14. doi: 10.1002/jmri.26004. [Epub ahead of print]

PMID:
29537720
3.

Significant Anatomy Detection Through Sparse Classification: A Comparative Study.

Zhang L, Cobzas D, Wilman AH, Kong L.

IEEE Trans Med Imaging. 2018 Jan;37(1):128-137. doi: 10.1109/TMI.2017.2735239. Epub 2017 Aug 2.

PMID:
28783628
4.

Progressive iron accumulation across multiple sclerosis phenotypes revealed by sparse classification of deep gray matter.

Elkady AM, Cobzas D, Sun H, Blevins G, Wilman AH.

J Magn Reson Imaging. 2017 Nov;46(5):1464-1473. doi: 10.1002/jmri.25682. Epub 2017 Mar 16.

PMID:
28301067
5.

Cognitive Implications of Deep Gray Matter Iron in Multiple Sclerosis.

Fujiwara E, Kmech JA, Cobzas D, Sun H, Seres P, Blevins G, Wilman AH.

AJNR Am J Neuroradiol. 2017 May;38(5):942-948. doi: 10.3174/ajnr.A5109. Epub 2017 Feb 23.

6.

Body Composition Assessment in Axial CT Images Using FEM-Based Automatic Segmentation of Skeletal Muscle.

Popuri K, Cobzas D, Esfandiari N, Baracos V, Jägersand M.

IEEE Trans Med Imaging. 2016 Feb;35(2):512-20. doi: 10.1109/TMI.2015.2479252. Epub 2015 Sep 22.

PMID:
26415164
7.

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. Epub 2015 May 18.

PMID:
25980643
8.

Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.

Rudyanto RD, Kerkstra S, van Rikxoort EM, Fetita C, Brillet PY, Lefevre C, Xue W, Zhu X, Liang J, Öksüz I, Ünay D, Kadipaşaoğlu K, Estépar RS, Ross JC, Washko GR, Prieto JC, Hoyos MH, Orkisz M, Meine H, Hüllebrand M, Stöcker C, Mir FL, Naranjo V, Villanueva E, Staring M, Xiao C, Stoel BC, Fabijanska A, Smistad E, Elster AC, Lindseth F, Foruzan AH, Kiros R, Popuri K, Cobzas D, Jimenez-Carretero D, Santos A, Ledesma-Carbayo MJ, Helmberger M, Urschler M, Pienn M, Bosboom DG, Campo A, Prokop M, de Jong PA, Ortiz-de-Solorzano C, Muñoz-Barrutia A, van Ginneken B.

Med Image Anal. 2014 Oct;18(7):1217-32. doi: 10.1016/j.media.2014.07.003. Epub 2014 Jul 23.

9.

A variational formulation for discrete registration.

Popuri K, Cobzas D, Jägersand M.

Med Image Comput Comput Assist Interv. 2013;16(Pt 3):187-94.

PMID:
24505760
10.

Tumor invasion margin on the Riemannian space of brain fibers.

Mosayebi P, Cobzas D, Murtha A, Jagersand M.

Med Image Anal. 2012 Feb;16(2):361-73. doi: 10.1016/j.media.2011.10.001. Epub 2011 Nov 15.

PMID:
22154876
11.

Random walks for deformable image registration.

Cobzas D, Sen A.

Med Image Comput Comput Assist Interv. 2011;14(Pt 2):557-65.

PMID:
21995073
12.

3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

Popuri K, Cobzas D, Murtha A, Jägersand M.

Int J Comput Assist Radiol Surg. 2012 Jul;7(4):493-506. doi: 10.1007/s11548-011-0649-2. Epub 2011 Aug 11.

PMID:
21833491
13.

Tumor invasion margin on the Riemannian space of brain fibers.

Cobzas D, Mosayebi P, Murtha A, Jagersand M.

Med Image Comput Comput Assist Interv. 2009;12(Pt 2):531-9.

PMID:
20426153

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