159 related articles for article (PubMed ID: 34531615)
21. Undersampled single-shell to MSMT fODF reconstruction using CNN-based ODE solver.
Jha RR; Kumar BVR; Pathak SK; Schneider W; Bhavsar A; Nigam A
Comput Methods Programs Biomed; 2023 Mar; 230():107339. PubMed ID: 36682110
[TBL] [Abstract][Full Text] [Related]
22. Enhancing the estimation of fiber orientation distributions using convolutional neural networks.
Lucena O; Vos SB; Vakharia V; Duncan J; Ashkan K; Sparks R; Ourselin S
Comput Biol Med; 2021 Aug; 135():104643. PubMed ID: 34280774
[TBL] [Abstract][Full Text] [Related]
23. Non-Negative Spherical Deconvolution (NNSD) for estimation of fiber Orientation Distribution Function in single-/multi-shell diffusion MRI.
Cheng J; Deriche R; Jiang T; Shen D; Yap PT
Neuroimage; 2014 Nov; 101():750-64. PubMed ID: 25108182
[TBL] [Abstract][Full Text] [Related]
24. The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion magnetic resonance imaging data.
Guo F; de Luca A; Parker G; Jones DK; Viergever MA; Leemans A; Tax CMW
Hum Brain Mapp; 2021 Feb; 42(2):367-383. PubMed ID: 33035372
[TBL] [Abstract][Full Text] [Related]
25. NVAM-Net: deep learning networks for reconstructing high-quality fiber orientation distributions.
Li J; Ai L; Yao R
Neuroradiology; 2024 Jul; 66(7):1177-1187. PubMed ID: 38563964
[TBL] [Abstract][Full Text] [Related]
26. Single-shell to multi-shell dMRI transformation using spatial and volumetric multilevel hierarchical reconstruction framework.
Jha RR; Jaswal G; Bhavsar A; Nigam A
Magn Reson Imaging; 2022 Apr; 87():133-156. PubMed ID: 35017034
[TBL] [Abstract][Full Text] [Related]
27. Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data.
Tax CM; Jeurissen B; Vos SB; Viergever MA; Leemans A
Neuroimage; 2014 Feb; 86():67-80. PubMed ID: 23927905
[TBL] [Abstract][Full Text] [Related]
28. Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.
Jeurissen B; Szczepankiewicz F
Neuroimage; 2021 Dec; 245():118717. PubMed ID: 34775006
[TBL] [Abstract][Full Text] [Related]
29. Isotropic non-white matter partial volume effects in constrained spherical deconvolution.
Roine T; Jeurissen B; Perrone D; Aelterman J; Leemans A; Philips W; Sijbers J
Front Neuroinform; 2014; 8():28. PubMed ID: 24734018
[TBL] [Abstract][Full Text] [Related]
30. Linking spherical mean diffusion weighted signal with intra-axonal volume fraction.
Li H; Chow HM; Chugani DC; Chugani HT
Magn Reson Imaging; 2019 Apr; 57():75-82. PubMed ID: 30439515
[TBL] [Abstract][Full Text] [Related]
31. Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution.
Jeurissen B; Leemans A; Jones DK; Tournier JD; Sijbers J
Hum Brain Mapp; 2011 Mar; 32(3):461-79. PubMed ID: 21319270
[TBL] [Abstract][Full Text] [Related]
32. Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution.
Portegies JM; Fick RH; Sanguinetti GR; Meesters SP; Girard G; Duits R
PLoS One; 2015; 10(10):e0138122. PubMed ID: 26465600
[TBL] [Abstract][Full Text] [Related]
33. Comparison of probabilistic tractography and tract-based spatial statistics for assessing optic radiation damage in patients with autoimmune inflammatory disorders of the central nervous system.
Kuchling J; Backner Y; Oertel FC; Raz N; Bellmann-Strobl J; Ruprecht K; Paul F; Levin N; Brandt AU; Scheel M
Neuroimage Clin; 2018; 19():538-550. PubMed ID: 29984162
[TBL] [Abstract][Full Text] [Related]
34. Probabilistic versus deterministic tractography for delineation of the cortico-subthalamic hyperdirect pathway in patients with Parkinson disease selected for deep brain stimulation.
Petersen MV; Lund TE; Sunde N; Frandsen J; Rosendal F; Juul N; Østergaard K
J Neurosurg; 2017 May; 126(5):1657-1668. PubMed ID: 27392264
[TBL] [Abstract][Full Text] [Related]
35. A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2
Ma R; Akçakaya M; Moeller S; Auerbach E; Uğurbil K; Van de Moortele PF
Neuroimage; 2020 Aug; 216():116861. PubMed ID: 32305565
[TBL] [Abstract][Full Text] [Related]
36. Fiber Orientation and Compartment Parameter Estimation From Multi-Shell Diffusion Imaging.
Tran G; Shi Y
IEEE Trans Med Imaging; 2015 Nov; 34(11):2320-32. PubMed ID: 25966471
[TBL] [Abstract][Full Text] [Related]
37. Learning to estimate the fiber orientation distribution function from diffusion-weighted MRI.
Karimi D; Vasung L; Jaimes C; Machado-Rivas F; Warfield SK; Gholipour A
Neuroimage; 2021 Oct; 239():118316. PubMed ID: 34182101
[TBL] [Abstract][Full Text] [Related]
38. Histological validation of diffusion MRI fiber orientation distributions and dispersion.
Schilling KG; Janve V; Gao Y; Stepniewska I; Landman BA; Anderson AW
Neuroimage; 2018 Jan; 165():200-221. PubMed ID: 29074279
[TBL] [Abstract][Full Text] [Related]
39. Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data.
Elaldi A; Dey N; Kim H; Gerig G
Inf Process Med Imaging; 2021 Jun; 12729():267-278. PubMed ID: 37576905
[TBL] [Abstract][Full Text] [Related]
40. Comparison of 3D orientation distribution functions measured with confocal microscopy and diffusion MRI.
Schilling K; Janve V; Gao Y; Stepniewska I; Landman BA; Anderson AW
Neuroimage; 2016 Apr; 129():185-197. PubMed ID: 26804781
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
