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ECR 2018 / C-1387
Morphological brain images acquired with a tilting MRI scanner: feasibility and quality evaluations
Congress: ECR 2018
Poster No.: C-1387
Type: Scientific Exhibit
Keywords: Anatomy, Neuroradiology brain, MR, Segmentation, Education and training
Authors: M. Laganà1, S. Carrara1, M. Olmi2, M. Cresti2, L. Forzoni3, P. Cecconi4; 1Milano/IT, 2Genova/IT, 3Firenze/IT, 4Como (CO)/IT
DOI:10.1594/ecr2018/C-1387

References

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[2] M. Lustig, D. Donoho, J. M. Pauly. Sparse MRI: The Application of Compressed Sensing for Rapid MR Imaging. Magnetic Resonance in Medicine 58:1182–1195 (2007)

[3] S.M. Smith. Fast robust automated brain extraction. Hum Brain Mapp 2002 Nov;17(3):143-155.

[4] S.M. Smith, Y. Zhang, M. Jenkinson, J. Chen, P.M. Matthews, A. Federico, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002 Sep;17:479-489.

[5] B.Patenaude, S.M.Smith, D.Kennedy, and M. Jenkinson. A Bayesian Model of Shape and Appearance for Subcortical Brain NeuroImage, 56:907-922, 2011.

[6] M. Laganà, M. Rovaris, A. Ceccarelli, C. Venturelli, S. Marini and G. Baselli. DTI Parameter Optimisation for Acquisition at 1.5T: SNR Analysis and Clinical Application. Computational Intelligence and Neuroscience 2010:254032 (2010)

[7] M.G. Dwyer, N.P. Bergsland, R. Zivadinov. Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model. Neuroimage 2014.

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