1
|
Johansen-Berg H and Behrens T: Diffusion
MRI. Academic Press; New York, NY, USA: 2nd. 2013
|
2
|
Peled S and Yeshurun Y: Superresolution in
MRI: Application to human white matter fiber tract visualization by
diffusion tensor imaging. Magn Reson Med. 45:29–35. 2001.
View Article : Google Scholar : PubMed/NCBI
|
3
|
Alexander AL, Hasan KM, Lazar M, Tsuruda
JS and Parker DL: Analysis of partial volume effects in
diffusion-tensor MRI. Magn Reson Med. 45:770–780. 2001. View Article : Google Scholar : PubMed/NCBI
|
4
|
Mori S and van Zijl PC: Fiber tracking:
Principles and strategies - a technical review. NMR Biomed.
15:468–480. 2002. View Article : Google Scholar : PubMed/NCBI
|
5
|
Miller KL, Stagg CJ, Douaud G, Jbabdi S,
Smith SM, Behrens TE, Jenkinson M, Chance SA, Esiri MM, Voets NL,
et al: Diffusion imaging of whole, post-mortem human brains on a
clinical MRI scanner. Neuroimage. 57:167–181. 2011. View Article : Google Scholar : PubMed/NCBI
|
6
|
Hu X and Norris DG: Advances in high-field
magnetic resonance imaging. Annu Rev Biomed Eng. 6:1572004.
View Article : Google Scholar : PubMed/NCBI
|
7
|
Kimmlingen R, Eberlein E, Gebhardt M,
Hartinger B, Ladebeck R, Lazar R, Reese T, Riegler J, Schmitt F,
Sorensen GA, et al: An easy to exchange high performance head
gradient insert for a 3T whole body MRI system: First results. Proc
Intl Soc Mag Reson Med. 11:pp. 16302004;
|
8
|
Scherrer B, Gholipour A and Warfield SK:
Super-resolution reconstruction to increase the spatial resolution
of diffusion weighted images from orthogonal anisotropic
acquisitions. Med Image Anal. 16:1465–1476. 2012. View Article : Google Scholar : PubMed/NCBI
|
9
|
Irani M and Peleg S: Motion analysis for
image enhancement: Resolution, occlusion and transparency. J Vis
Commun Image R. 4:324–335. 1993. View Article : Google Scholar
|
10
|
Arsigny V, Fillard P, Pennec X and Ayache
N: Log-Euclidean metrics for fast and simple calculus on diffusion
tensors. Magn Reson Med. 56:411–421. 2006. View Article : Google Scholar : PubMed/NCBI
|
11
|
Calamante F, Tournier JD, Jackson GD and
Connelly A: Track-density imaging (TDI): Super-resolution white
matter imaging using whole-brain track-density mapping. Neuroimage.
53:1233–1243. 2010. View Article : Google Scholar : PubMed/NCBI
|
12
|
Manjón JV, Coupé P, Buades A, Fonov V,
Collins D Louis and Robles M: Non-local MRI upsampling. Med Image
Anal. 14:784–792. 2010. View Article : Google Scholar : PubMed/NCBI
|
13
|
Rueda A, Malpica N and Romero E:
Single-image super-resolution of brain MR images using overcomplete
dictionaries. Med Image Anal. 17:113–132. 2013. View Article : Google Scholar : PubMed/NCBI
|
14
|
Fillard P, Pennec X, Arsigny V and Ayache
N: Clinical DT-MRI estimation, smoothing and fiber tracking with
log-euclidean metrics. IEEE Trans Med Imaging. 26:1472–1482. 2007.
View Article : Google Scholar : PubMed/NCBI
|
15
|
Tristán-Vega A, Westin CF and
Aja-Fernández S: A new methodology for the estimation of fiber
populations in the white matter of the brain with the Funk-Radon
transform. Neuroimage. 49:1301–1315. 2010. View Article : Google Scholar : PubMed/NCBI
|
16
|
Tristán-Vega A and Aja-Fernández S: DWI
filtering using joint information for DTI and HARDI. Med Image
Anal. 14:205–218. 2010. View Article : Google Scholar : PubMed/NCBI
|
17
|
Yang Z and He P: Non-local diffusion
weighted image super-resolution using collaborative joint
information. Digital Signal Processing (DSP) IEEE. 1–273. 2015.
|
18
|
Buades A, Coll B and Morel JM: A non-local
algorithm for image denoising. Computer Vision and Pattern
Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on.
2005; View Article : Google Scholar
|
19
|
Manjón JV, Coupé P, Buades A, Collins D
Louis and Robles M: New methods for MRI denoising based on
sparseness and self-similarity. Med Image Anal. 16:18–27. 2012.
View Article : Google Scholar : PubMed/NCBI
|
20
|
Lou Y, Favaro P, Soatto S and Bertozzi A:
Nonlocal similarity image filtering. In Image Analysis and
Processing - ICIAP 2009–15th International Conference, Proceedings.
5716:pp. 62–71. 2009; View Article : Google Scholar
|
21
|
Wu X, Liu S, Wu M, Sun H, Zhou J, Gong Q
and Ding Z: Nonlocal denoising using anisotropic structure tensor
for 3D MRI. Med Phys. 40:1019042013. View Article : Google Scholar : PubMed/NCBI
|
22
|
Rousseau F: Brain hallucination. Computer
Vision-ECCV. 5302:497–508. 2008.
|
23
|
Rousseau F: Alzheimer's Disease
Neuroimaging Initiative: A non-local approach for image
super-resolution using intermodality priors. Med Image Anal.
14:594–605. 2010. View Article : Google Scholar : PubMed/NCBI
|
24
|
Coupé P, Manjón JV, Chamberland M,
Descoteaux M and Hiba B: Collaborative patch-based super-resolution
for diffusion-weighted images. Neuroimage. 83:245–261. 2013.
View Article : Google Scholar : PubMed/NCBI
|
25
|
Banerjee J and Jawahar CV:
Super-resolution of text images using edge-directed tangent field.
DAS. 76–83. 2008.
|
26
|
Tournier JD, Calamante F and Connelly A:
MRtrix: Diffusion tractography in crossing fiber regions. Int J
Imaging Syst Technol. 22:53–66. 2012. View Article : Google Scholar
|
27
|
Raffelt D, Tournier JD, Rose S, Ridgway
GR, Henderson R, Crozier S, Salvado O and Connelly A: Apparent
fibre density: A novel measure for the analysis of
diffusion-weighted magnetic resonance images. Neuroimage.
59:3976–3994. 2012. View Article : Google Scholar : PubMed/NCBI
|
28
|
Daducci A, Canales-Rodríguez EJ,
Descoteaux M, Garyfallidis E, Gur Y, Lin YC, Mani M, Merlet S,
Paquette M, Ramirez-Manzanares A, et al: Quantitative comparison of
reconstruction methods for intra-voxel fiber recovery from
diffusion MRI. IEEE Trans Med Imaging. 33:384–399. 2014. View Article : Google Scholar : PubMed/NCBI
|
29
|
Wang Z, Bovik AC, Sheikh HR and Simoncelli
EP: Image quality assessment: From error visibility to structural
similarity. IEEE Trans on Image Process. 13:600–612. 2004.
View Article : Google Scholar
|
30
|
Fillard P, Descoteaux M, Goh A, Gouttard
S, Jeurissen B, Malcolm J, Ramirez-Manzanares A, Reisert M, Sakaie
K, Tensaouti F, et al: Quantitative evaluation of 10 tractography
algorithms on a realistic diffusion MR phantom. Neuroimage.
56:220–234. 2011. View Article : Google Scholar : PubMed/NCBI
|
31
|
Poupon C, Rieul B, Kezele I, Perrin M,
Poupon F and Mangin JF: New diffusion phantoms dedicated to the
study and validation of high-angular resolution diffusion imaging
(HARDI) models. Magn Reson Med. 60:1276–1283. 2008. View Article : Google Scholar : PubMed/NCBI
|
32
|
Basser PJ, Matiello J and Bihan DL:
Estimation of the effective self-diffusion tensor from the NMR spin
echo. J Magn Reson B. 103:247–254. 1994. View Article : Google Scholar : PubMed/NCBI
|
33
|
Tournier JD, Calamante F and Connelly A:
Robust determination of the fibre orientation distribution in
diffusion MRI: Non-negativity constrained super-resolved spherical
deconvolution. Neuroimage. 35:1459–1472. 2007. View Article : Google Scholar : PubMed/NCBI
|
34
|
Basser PJ, Mattielo J and LeBihan D:
Estimation of the effective self-diffusion tensor from the NMR spin
echo. J Magn Reson B. 103:247–254. 1994. View Article : Google Scholar : PubMed/NCBI
|
35
|
Smith SM, Jenkinson M, Woolrich MW,
Beckmann CF, Behrens TE, Johansen-Berg H, Bannister PR, De Luca M,
Drobnjak I, Flitney DE, et al: Advances in functional and
structural MR image analysis and implementation as FSL. Neuroimage.
23 Suppl 1:S208–S219. 1994. View Article : Google Scholar
|