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Showing 1 to 12 of 35 entries
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DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30.

Proceedings. IEEE International Symposium on Biomedical Imaging

Dennis EL, Jahanshad N, Toga AW, McMahon KL, de Zubicaray GI, Hickie I, Wright MJ, Thompson PM.
PMID: 24827471
Proc IEEE Int Symp Biomed Imaging. 2013;624-627. doi: 10.1109/ISBI.2013.6556552.

The 'rich club' coefficient describes a phenomenon where a network's hubs (high-degree nodes) are on average more intensely interconnected than lower-degree nodes. Networks with rich clubs often have an efficient, higher-order organization, but we do not yet know how...

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Dennis EL, Jahanshad N, Toga AW, et al. DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proc IEEE Int Symp Biomed Imaging. 2013;624-627doi: 10.1109/ISBI.2013.6556552.
Dennis, E. L., Jahanshad, N., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., Hickie, I., Wright, M. J., & Thompson, P. M. (2013). DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proceedings. IEEE International Symposium on Biomedical Imaging, 624-627. https://doi.org/10.1109/ISBI.2013.6556552
Dennis, Emily L, et al. "DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2013): 624-627. doi: https://doi.org/10.1109/ISBI.2013.6556552
Dennis EL, Jahanshad N, Toga AW, McMahon KL, de Zubicaray GI, Hickie I, Wright MJ, Thompson PM. DEVELOPMENT OF THE "RICH CLUB" IN BRAIN CONNECTIVITY NETWORKS FROM 438 ADOLESCENTS & ADULTS AGED 12 TO 30. Proc IEEE Int Symp Biomed Imaging. 2013;624-627. doi: 10.1109/ISBI.2013.6556552. PMID: 24827471; PMCID: PMC4017916.
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Reprint of: Mapping connectivity in the developing brain.

International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience

Dennis EL, Thompson PM.
PMID: 24295552
Int J Dev Neurosci. 2014 Feb;32:41-57. doi: 10.1016/j.ijdevneu.2013.11.005. Epub 2013 Dec 02.

Recently, there has been a wealth of research into structural and functional brain connectivity, and how they change over development. While we are far from a complete understanding, these studies have yielded important insights into human brain development. There...

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Dennis EL, Thompson PM. Reprint of: Mapping connectivity in the developing brain. Int J Dev Neurosci. 2013;32:41-57doi: 10.1016/j.ijdevneu.2013.11.005.
Dennis, E. L., & Thompson, P. M. (2014). Reprint of: Mapping connectivity in the developing brain. International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience, 3241-57. https://doi.org/10.1016/j.ijdevneu.2013.11.005
Dennis, Emily L, and Thompson, Paul M. "Reprint of: Mapping connectivity in the developing brain." International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience vol. 32 (2014): 41-57. doi: https://doi.org/10.1016/j.ijdevneu.2013.11.005
Dennis EL, Thompson PM. Reprint of: Mapping connectivity in the developing brain. Int J Dev Neurosci. 2014 Feb;32:41-57. doi: 10.1016/j.ijdevneu.2013.11.005. Epub 2013 Dec 02. PMID: 24295552; PMCID: PMC4442620.
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Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines.

Journal of medical imaging (Bellingham, Wash.)

Koran ME, Thornton-Wells TA, Jahanshad N, Glahn DC, Thompson PM, Blangero J, Nichols TE, Kochunov P, Landman BA.
PMID: 25558465
J Med Imaging (Bellingham). 2014 Jun 27;1(1):014005. doi: 10.1117/1.JMI.1.1.014005.

Imaging genetics is an emerging methodological field that combines genetic information with medical imaging-derived metrics to understand how genetic factors impact observable phenotypes. In order for a trait to be a reasonable phenotype in an imaging genetics study, it...

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Koran ME, Thornton-Wells TA, Jahanshad N, et al. Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. J Med Imaging (Bellingham). 2014;1(1):014005doi: 10.1117/1.JMI.1.1.014005.
Koran, M. E., Thornton-Wells, T. A., Jahanshad, N., Glahn, D. C., Thompson, P. M., Blangero, J., Nichols, T. E., Kochunov, P., & Landman, B. A. (2014). Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. Journal of medical imaging (Bellingham, Wash.), 1(1), 014005. https://doi.org/10.1117/1.JMI.1.1.014005
Koran, Mary Ellen, et al. "Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines." Journal of medical imaging (Bellingham, Wash.) vol. 1,1 (2014): 014005. doi: https://doi.org/10.1117/1.JMI.1.1.014005
Koran ME, Thornton-Wells TA, Jahanshad N, Glahn DC, Thompson PM, Blangero J, Nichols TE, Kochunov P, Landman BA. Impact of family structure and common environment on heritability estimation for neuroimaging genetics studies using Sequential Oligogenic Linkage Analysis Routines. J Med Imaging (Bellingham). 2014 Jun 27;1(1):014005. doi: 10.1117/1.JMI.1.1.014005. PMID: 25558465; PMCID: PMC4281883.
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Sparse Bayesian Inference of White Matter Fiber Orientations from Compressed Multi-resolution Diffusion MRI.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

Pisharady PK, Duarte-Carvajalino JM, Sotiropoulos SN, Sapiro G, Lenglet C.
PMID: 28845484
Med Image Comput Comput Assist Interv. 2015 Oct;9349:117-124. doi: 10.1007/978-3-319-24553-9_15. Epub 2015 Nov 18.

The RubiX [1] algorithm combines high SNR characteristics of low resolution data with high spacial specificity of high resolution data, to extract microstructural tissue parameters from diffusion MRI. In this paper we focus on estimating crossing fiber orientations and...

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Pisharady PK, Duarte-Carvajalino JM, Sotiropoulos SN, et al. Sparse Bayesian Inference of White Matter Fiber Orientations from Compressed Multi-resolution Diffusion MRI. Med Image Comput Comput Assist Interv. 2015;9349:117-124doi: 10.1007/978-3-319-24553-9_15.
Pisharady, P. K., Duarte-Carvajalino, J. M., Sotiropoulos, S. N., Sapiro, G., & Lenglet, C. (2015). Sparse Bayesian Inference of White Matter Fiber Orientations from Compressed Multi-resolution Diffusion MRI. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 9349117-124. https://doi.org/10.1007/978-3-319-24553-9_15
Pisharady, Pramod Kumar, et al. "Sparse Bayesian Inference of White Matter Fiber Orientations from Compressed Multi-resolution Diffusion MRI." Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention vol. 9349 (2015): 117-124. doi: https://doi.org/10.1007/978-3-319-24553-9_15
Pisharady PK, Duarte-Carvajalino JM, Sotiropoulos SN, Sapiro G, Lenglet C. Sparse Bayesian Inference of White Matter Fiber Orientations from Compressed Multi-resolution Diffusion MRI. Med Image Comput Comput Assist Interv. 2015 Oct;9349:117-124. doi: 10.1007/978-3-319-24553-9_15. Epub 2015 Nov 18. PMID: 28845484; PMCID: PMC5568854.
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A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing

Mo C, Ye Z, Ke H, Lu T, Canida T, Liu S, Wu Q, Zhao Z, Ma Y, Hong LE, Kochunov P, Ma T, Chen S.
PMID: 34890138
Pac Symp Biocomput. 2022;27:73-84.

The advent of simultaneously collected imaging-genetics data in large study cohorts provides an unprecedented opportunity to assess the causal effect of brain imaging traits on externally measured experimental results (e.g., cognitive tests) by treating genetic variants as instrumental variables....

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Mo C, Ye Z, Ke H, et al. A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures. Pac Symp Biocomput. 2022;27:73-84
Mo, C., Ye, Z., Ke, H., Lu, T., Canida, T., Liu, S., Wu, Q., Zhao, Z., Ma, Y., Hong, L. E., Kochunov, P., Ma, T., & Chen, S. (2022). A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2773-84.
Mo, Chen, et al. "A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures." Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing vol. 27 (2022): 73-84.
Mo C, Ye Z, Ke H, Lu T, Canida T, Liu S, Wu Q, Zhao Z, Ma Y, Hong LE, Kochunov P, Ma T, Chen S. A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures. Pac Symp Biocomput. 2022;27:73-84. PMID: 34890138; PMCID: PMC8669774.
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CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS.

Proceedings. IEEE International Symposium on Biomedical Imaging

Dennis EL, Jahanshad N, Toga AW, Johnson K, McMahon KL, de Zubicaray GI, Martin NG, Hickie IB, Wright MJ, Thompson PM.
PMID: 22903354
Proc IEEE Int Symp Biomed Imaging. 2012;904-908. doi: 10.1109/ISBI.2012.6235695.

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but...

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Dennis EL, Jahanshad N, Toga AW, et al. CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proc IEEE Int Symp Biomed Imaging. 2012;904-908doi: 10.1109/ISBI.2012.6235695.
Dennis, E. L., Jahanshad, N., Toga, A. W., Johnson, K., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Hickie, I. B., Wright, M. J., & Thompson, P. M. (2012). CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proceedings. IEEE International Symposium on Biomedical Imaging, 904-908. https://doi.org/10.1109/ISBI.2012.6235695
Dennis, Emily L, et al. "CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2012): 904-908. doi: https://doi.org/10.1109/ISBI.2012.6235695
Dennis EL, Jahanshad N, Toga AW, Johnson K, McMahon KL, de Zubicaray GI, Martin NG, Hickie IB, Wright MJ, Thompson PM. CHANGES IN ANATOMICAL BRAIN CONNECTIVITY BETWEEN AGES 12 AND 30: A HARDI STUDY OF 467 ADOLESCENTS AND ADULTS. Proc IEEE Int Symp Biomed Imaging. 2012;904-908. doi: 10.1109/ISBI.2012.6235695. PMID: 22903354; PMCID: PMC3420974.
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Asymmetric and Symmetric Unbiased Image Registration: Statistical Assessment of Performance.

Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops

Yanovsky I, Thompson PM, Osher S, Leow AD.
PMID: 29152411
Conf Comput Vis Pattern Recognit Workshops. 2008 Jun;2008. doi: 10.1109/CVPRW.2008.4562988. Epub 2008 Jul 15.

Measures of brain changes can be computed from sequential MRI scans, providing valuable information on disease progression for neuroscientific studies and clinical trials. Tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of...

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Yanovsky I, Thompson PM, Osher S, et al. Asymmetric and Symmetric Unbiased Image Registration: Statistical Assessment of Performance. Conf Comput Vis Pattern Recognit Workshops. 2008;2008doi: 10.1109/CVPRW.2008.4562988.
Yanovsky, I., Thompson, P. M., Osher, S., & Leow, A. D. (2008). Asymmetric and Symmetric Unbiased Image Registration: Statistical Assessment of Performance. Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops, 2008. https://doi.org/10.1109/CVPRW.2008.4562988
Yanovsky, Igor, et al. "Asymmetric and Symmetric Unbiased Image Registration: Statistical Assessment of Performance." Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops vol. 2008 (2008). doi: https://doi.org/10.1109/CVPRW.2008.4562988
Yanovsky I, Thompson PM, Osher S, Leow AD. Asymmetric and Symmetric Unbiased Image Registration: Statistical Assessment of Performance. Conf Comput Vis Pattern Recognit Workshops. 2008 Jun;2008. doi: 10.1109/CVPRW.2008.4562988. Epub 2008 Jul 15. PMID: 29152411; PMCID: PMC5687076.
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Genetics of Path Lengths in Brain Connectivity Networks: HARDI-Based Maps in 457 Adults.

Multimodal brain image analysis : second International Workshop, MBIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1-5, 2012 : proceedings. MBIA (Workshop) (2nd : 2012 : Nice, France)

Jahanshad N, Prasad G, Toga AW, McMahon KL, de Zubicaray GI, Martin NG, Wright MJ, Thompson PM.
PMID: 25584366
Multimodal Brain Image Anal (2012). 2012;7509:29-40. doi: 10.1007/978-3-642-33530-3_3.

Brain connectivity analyses are increasingly popular for investigating organization. Many connectivity measures including path lengths are generally defined as the number of nodes traversed to connect a node in a graph to the others. Despite its name, path length...

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Jahanshad N, Prasad G, Toga AW, et al. Genetics of Path Lengths in Brain Connectivity Networks: HARDI-Based Maps in 457 Adults. Multimodal Brain Image Anal (2012). 2012;7509:29-40doi: 10.1007/978-3-642-33530-3_3.
Jahanshad, N., Prasad, G., Toga, A. W., McMahon, K. L., de Zubicaray, G. I., Martin, N. G., Wright, M. J., & Thompson, P. M. (2012). Genetics of Path Lengths in Brain Connectivity Networks: HARDI-Based Maps in 457 Adults. Multimodal brain image analysis : second International Workshop, MBIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1-5, 2012 : proceedings. MBIA (Workshop) (2nd : 2012 : Nice, France), 750929-40. https://doi.org/10.1007/978-3-642-33530-3_3
Jahanshad, Neda, et al. "Genetics of Path Lengths in Brain Connectivity Networks: HARDI-Based Maps in 457 Adults." Multimodal brain image analysis : second International Workshop, MBIA 2012, held in conjunction with MICCAI 2012, Nice, France, October 1-5, 2012 : proceedings. MBIA (Workshop) (2nd : 2012 : Nice, France) vol. 7509 (2012): 29-40. doi: https://doi.org/10.1007/978-3-642-33530-3_3
Jahanshad N, Prasad G, Toga AW, McMahon KL, de Zubicaray GI, Martin NG, Wright MJ, Thompson PM. Genetics of Path Lengths in Brain Connectivity Networks: HARDI-Based Maps in 457 Adults. Multimodal Brain Image Anal (2012). 2012;7509:29-40. doi: 10.1007/978-3-642-33530-3_3. PMID: 25584366; PMCID: PMC4288784.
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SKULL-STRIPPING WITH DEFORMABLE ORGANISMS.

Proceedings. IEEE International Symposium on Biomedical Imaging

Prasad G, Joshi AA, Thompson PM, Toga AW, Shattuck DW, Terzopoulos D.
PMID: 25277660
Proc IEEE Int Symp Biomed Imaging. 2011;1662-1665. doi: 10.1109/ISBI.2011.5872723.

Segmenting brain from non-brain tissue within magnetic resonance (MR) images of the human head, also known as skull-stripping, is a critical processing step in the analysis of neuroimaging data. Though many algorithms have been developed to address this problem,...

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Prasad G, Joshi AA, Thompson PM, et al. SKULL-STRIPPING WITH DEFORMABLE ORGANISMS. Proc IEEE Int Symp Biomed Imaging. 2011;1662-1665doi: 10.1109/ISBI.2011.5872723.
Prasad, G., Joshi, A. A., Thompson, P. M., Toga, A. W., Shattuck, D. W., & Terzopoulos, D. (2011). SKULL-STRIPPING WITH DEFORMABLE ORGANISMS. Proceedings. IEEE International Symposium on Biomedical Imaging, 1662-1665. https://doi.org/10.1109/ISBI.2011.5872723
Prasad, Gautam, et al. "SKULL-STRIPPING WITH DEFORMABLE ORGANISMS." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2011): 1662-1665. doi: https://doi.org/10.1109/ISBI.2011.5872723
Prasad G, Joshi AA, Thompson PM, Toga AW, Shattuck DW, Terzopoulos D. SKULL-STRIPPING WITH DEFORMABLE ORGANISMS. Proc IEEE Int Symp Biomed Imaging. 2011;1662-1665. doi: 10.1109/ISBI.2011.5872723. PMID: 25277660; PMCID: PMC4179287.
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White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study.

NeuroImage. Clinical

Barysheva M, Jahanshad N, Foland-Ross L, Altshuler LL, Thompson PM.
PMID: 24179807
Neuroimage Clin. 2013 Apr 05;2:558-68. doi: 10.1016/j.nicl.2013.03.016. eCollection 2013.

BACKGROUND: Bipolar disorder (BD) is a chronic mental illness characterized by severe disruptions in mood and cognition. Diffusion tensor imaging (DTI) studies suggest that white matter (WM) tract abnormalities may contribute to the clinical hallmarks of the disorder. Using...

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Barysheva M, Jahanshad N, Foland-Ross L, et al. White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study. Neuroimage Clin. 2013;2:558-68doi: 10.1016/j.nicl.2013.03.016.
Barysheva, M., Jahanshad, N., Foland-Ross, L., Altshuler, L. L., & Thompson, P. M. (2013). White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study. NeuroImage. Clinical, 2558-68. https://doi.org/10.1016/j.nicl.2013.03.016
Barysheva, Marina, et al. "White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study." NeuroImage. Clinical vol. 2 (2013): 558-68. doi: https://doi.org/10.1016/j.nicl.2013.03.016
Barysheva M, Jahanshad N, Foland-Ross L, Altshuler LL, Thompson PM. White matter microstructural abnormalities in bipolar disorder: A whole brain diffusion tensor imaging study. Neuroimage Clin. 2013 Apr 05;2:558-68. doi: 10.1016/j.nicl.2013.03.016. eCollection 2013. PMID: 24179807; PMCID: PMC3777761.
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Multilocus genetic profiling to empower drug trials and predict brain atrophy.

NeuroImage. Clinical

Kohannim O, Hua X, Rajagopalan P, Hibar DP, Jahanshad N, Grill JD, Apostolova LG, Toga AW, Jack CR, Weiner MW, Thompson PM.
PMID: 24179834
Neuroimage Clin. 2013 Jun 13;2:827-35. doi: 10.1016/j.nicl.2013.05.007. eCollection 2013.

Designers of clinical trials for Alzheimer's disease (AD) and mild cognitive impairment (MCI) are actively considering structural and functional neuroimaging, cerebrospinal fluid and genetic biomarkers to reduce the sample sizes needed to detect therapeutic effects. Genetic pre-selection, however, has...

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Kohannim O, Hua X, Rajagopalan P, et al. Multilocus genetic profiling to empower drug trials and predict brain atrophy. Neuroimage Clin. 2013;2:827-35doi: 10.1016/j.nicl.2013.05.007.
Kohannim, O., Hua, X., Rajagopalan, P., Hibar, D. P., Jahanshad, N., Grill, J. D., Apostolova, L. G., Toga, A. W., Jack, C. R., Weiner, M. W., Thompson, P. M. (2013). Multilocus genetic profiling to empower drug trials and predict brain atrophy. NeuroImage. Clinical, 2827-35. https://doi.org/10.1016/j.nicl.2013.05.007
Kohannim, Omid, et al. "Multilocus genetic profiling to empower drug trials and predict brain atrophy." NeuroImage. Clinical vol. 2 (2013): 827-35. doi: https://doi.org/10.1016/j.nicl.2013.05.007
Kohannim O, Hua X, Rajagopalan P, Hibar DP, Jahanshad N, Grill JD, Apostolova LG, Toga AW, Jack CR, Weiner MW, Thompson PM. Multilocus genetic profiling to empower drug trials and predict brain atrophy. Neuroimage Clin. 2013 Jun 13;2:827-35. doi: 10.1016/j.nicl.2013.05.007. eCollection 2013. PMID: 24179834; PMCID: PMC3777716.
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GROUP ACTION INDUCED AVERAGING FOR HARDI PROCESSING.

Proceedings. IEEE International Symposium on Biomedical Imaging

Cetingül HE, Afsari B, Wright MJ, Thompson PM, Vidal R.
PMID: 22903055
Proc IEEE Int Symp Biomed Imaging. 2012;1389-1392. doi: 10.1109/ISBI.2012.6235827.

We consider the problem of processing high angular resolution diffusion images described by orientation distribution functions (ODFs). Prior work showed that several processing operations, e.g., averaging, interpolation and filtering, can be reduced to averaging in the space of ODFs....

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Cetingül HE, Afsari B, Wright MJ, et al. GROUP ACTION INDUCED AVERAGING FOR HARDI PROCESSING. Proc IEEE Int Symp Biomed Imaging. 2012;1389-1392doi: 10.1109/ISBI.2012.6235827.
Cetingül, H. E., Afsari, B., Wright, M. J., Thompson, P. M., & Vidal, R. (2012). GROUP ACTION INDUCED AVERAGING FOR HARDI PROCESSING. Proceedings. IEEE International Symposium on Biomedical Imaging, 1389-1392. https://doi.org/10.1109/ISBI.2012.6235827
Cetingül, H Ertan, et al. "GROUP ACTION INDUCED AVERAGING FOR HARDI PROCESSING." Proceedings. IEEE International Symposium on Biomedical Imaging vol. (2012): 1389-1392. doi: https://doi.org/10.1109/ISBI.2012.6235827
Cetingül HE, Afsari B, Wright MJ, Thompson PM, Vidal R. GROUP ACTION INDUCED AVERAGING FOR HARDI PROCESSING. Proc IEEE Int Symp Biomed Imaging. 2012;1389-1392. doi: 10.1109/ISBI.2012.6235827. PMID: 22903055; PMCID: PMC3420967.
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