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Documents dont le centre de recherche est "NeuroPoly - Laboratoire de Recherche en Neuroimagerie"

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Nombre de documents: 27

A

Alley, S., Gilbert, G., Wheeler-Kingshott, C. A. M. G., Samson, R. S., Grussu, F., Martin, A., Bannier, É., Callot, V., Smith, S. A., Xu, J., Dewey, B., Weber, K. A., Parrish, T., McLauren, D., Barker, G. J., Papinutto, N., Seif, M., Freund, P., Barry, R. L., ... Cohen-Adad, J. (juin 2018). Consensus acquisition protocol for quantitative MRI of the cervical spinal cord at 3T [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

B

Barral, J. K., Friedrich, M. G., & Stikov, N. (2018). Fundamentals of Cardiac T1 Mapping. Dans T1-Mapping in Myocardial Disease (14 pages). Lien externe

C

Cadotte, D. W., Akbar, M. A., Fehlings, M. G., Stroman, P. W., & Cohen-Adad, J. (2018). What Has Been Learned from Magnetic Resonance Imaging Examination of the Injured Human Spinal Cord: A Canadian Perspective. Journal of Neurotrauma, 35(16), 1942-1957. Lien externe

Calabrese, E., Adil, S. M., Cofer, G., Perone, C. S., Cohen-Adad, J., Lad, S. P., & Johnson, G. A. (2018). Postmortem diffusion MRI of the entire human spinal cord at microscopic resolution. NeuroImage: Clinical, 18, 963-971. Disponible

Campbell, J. S. W., Leppert, I. R., Narayanan, S., Boudreau, M., Duval, T., Cohen-Adad, J., Pike, G. B., & Stikov, N. (août 2016). Promise and pitfalls of g-ratio estimation with MRI [Communication écrite]. Workshop on Toward a Super-BigBrain - Promise and Pitfalls of Microstructural Imaging, Montréal, Canada. Publié dans Neuroimage, 182. Lien externe

Cohen-Adad, J. (août 2016). Microstructural imaging in the spinal cord and validation strategies [Communication écrite]. Workshop on Toward a Super-BigBrain - Promise and Pitfalls of Microstructural Imaging, Montréal, QC, Canada. Publié dans Neuroimage, 182. Lien externe

D

De Leener, B., Fonov, V. S., Collins, D. L., Callot, V., Stikov, N., & Cohen-Adad, J. (2018). PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. NeuroImage, 165, 170-179. Lien externe

De Tillieux, P., Topfer, R., Foias, A., Leroux, I., El Maâchi, I., Leblond, H., Stikov, N., & Cohen-Adad, J. (2018). A pneumatic phantom for mimicking respiration-induced artifacts in spinal MRI. Magnetic Resonance in Medicine, 79(1), 600-605. Lien externe

Duval, T., Leppert, I. R., Cabana, J.-F., Boudreau, M., Gagnon, I., Berestovoy, G., Cohen-Adad, J., & Stikov, N. (juin 2018). Quantitative MRI made easy with qMRLab [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

Duval, T., Smith, V., Stikov, N., Klawiter, E. C., & Cohen-Adad, J. (2018). Scan-rescan of axcaliber, macromolecular tissue volume, and g-ratio in the spinal cord. Magnetic Resonance in Medicine, 79(5), 2759-2765. Lien externe

E

Eden, D., Gros, C., Badji, A., Dupont, S., Maranzano, J., Zhuoquiong, R., Liu, Y., Talbott, J., Bannier, É., Kerbrat, A., Edan, G., Labauge, P., Callot, V., Pelletier, J., Audoin, B., Rasoanandrianina, H., Valsasina, P., Filippi, M., Bakshi, R., ... Cohen-Adad, J. (juin 2018). Spatial distribution of multiple sclerosis in the cervical cord [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

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Gros, C., Badji, A., Maranzano, J., Zhuoquiong, R., Yaou, L., Bannier, É., Kerbrat, A., Edan, G., Labauge, P., Callot, V., Pelletier, J., Audoin, B., Rasoanandrianina, H., Valsasina, P., Filippi, M., Bakshi, R., Tauhid, S., Prados, F., Yiannakas, M. C., ... Cohen-Adad, J. (juin 2018). Automatic MS lesion segmentation in the spinal cord using deep learning [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

Gros, C., De Leener, B., Dupont, S. M., Martin, A. R., Fehlings, M. G., Bakshi, R., Tummala, S., Auclair, V., McLaren, D. G., Callot, V., Cohen-Adad, J., & Sdika, M. (2018). Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Medical Image Analysis, 44, 215-227. Lien externe

H

Hagiwara, A., Hori, M., Cohen-Adad, J., Nakazawa, M., Suzuki, Y., Kasahara, A., Horita, M., Haruyama, T., Andica, C., Maekawa, T., Kamagata, K., Kumamaru, K. K., Abe, O., & Aoki, S. (2018). Linearity, Bias, Intrascanner Repeatability, and Interscanner Reproducibility of Quantitative Multidynamic Multiecho Sequence for Rapid Simultaneous Relaxometry at 3 T: A Validation Study With a Standardized Phantom and Healthy Controls. Investigative Radiology, 54(1), 39-47. Lien externe

L

Lee, L. E., Ljungberg, E., Shin, D., Figley, C. R., Vavasour, I. M., Rauscher, A., Cohen-Adad, J., Li, D. K. B., Traboulsee, A. L., MacKay, A. L., Lee, J., & Kolind, S. H. (2018). Inter-vendor reproducibility of myelin water imaging using a 3D gradient and spin echo sequence. Frontiers in Neuroscience, 12, 854 (8 pages). Disponible

Lévy, S., Guertin, M.-C., Khatibi, A., Mezer, A., Martinu, K., Chen, J. I., Stikov, N., Rainville, P., & Cohen-Adad, J. (2018). Correction: Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations. PLOS ONE, 13(6), e0199796. Lien externe

Lévy, S., Guertin, M.-C., Khatibi, A., Mezer, A., Martinu, K., Chen, J. I., Stikov, N., Rainville, P., & Cohen-Adad, J. (2018). Test-retest reliability of myelin imaging in the human spinal cord: Measurement errors versus region- and aging-induced variations. PLOS One, 13(1), e0189944 (25 pages). Disponible

Lopez Rios, N., Foias, A., Lodygensky, G., Dehaes, M., & Cohen-Adad, J. (2018). Size-adaptable 13-channel receive array for brain MRI in human neonates at 3T. NMR in Biomedicine, 31(8), 12 pages. Lien externe

M

Mangeat, G., Ouellette, R., Wabartha, M., Karrenbauer, V. D., Stikov, N., Warntjes, M., Mainero, C., Cohen-Adad, J., & Granberg, T. (juin 2018). Machine learning and rapid multi-parametric relaxometry can differentiate demyelinating disorders with high accuracy [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

Mangeat, G., Ouellette, R., Warntjes, M., Plattén, M., Engström Nordin, L., Stikov, N., Granberg, T., & Cohen-Adad, J. (juin 2018). Accuracy and precision of synthetic MRI [Affiche]. Joint annual meeting ISMRM - ESMRMB, Paris, France. Lien externe

Morozov, D., Lopez Rios, N., Duval, T., Foias, A., & Cohen-Adad, J. (2018). Effect of cardiac-related translational motion in diffusion MRI of the spinal cord. Magnetic Resonance Imaging, 50, 119-124. Lien externe

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Ouellette, R., Treaba, C. A., Granberg, T., Barletta, V., Herranz E, T., Mangeat, G., Mehndiratta, A., Tauhid, S., Yousuf, F., De Leener, B., Dupont, S., Sloane, J. A., Bakshi, R., Cohen-Adad, J., & Mainero, C. (octobre 2018). Characterization of multiple sclerosis grey and white matter pathology in the brain and spinal cord at 7 Tesla MRI [Affiche]. 34th Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS 2018), Berlin, Germany. Publié dans Multiple Sclerosis Journal, 24(2). Lien externe

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Paquin, M.-Ê., El Mendili, M. M., Gros, C., Dupont, S. M., Cohen-Adad, J., & Pradat, P. F. (2018). Spinal Cord Gray Matter Atrophy in Amyotrophic Lateral Sclerosis. American Journal of Neuroradiology, 39(1), 184-192. Lien externe

Perone, C. S., & Cohen-Adad, J. (septembre 2018). Deep semi-supervised segmentation with weight-averaged consistency targets [Communication écrite]. 4th International Workshop on Deep Learning in Medical Image Analysis (DLMIA 2018) and 8th International Workshop on Multimodal Learning for Clinical Decision Support (ML-CDS 2018), Granada, Spain. Lien externe

Perone, C. S., Calabrese, E., & Cohen-Adad, J. (2018). Spinal cord gray matter segmentation using deep dilated convolutions. Scientific Reports, 8(1), 5966 (13 pages). Disponible

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Topfer, R., Foias, A., Stikov, N., & Cohen-Adad, J. (2018). Real-time correction of respiration-induced distortions in the human spinal cord using a 24-channel shim array. Magnetic Resonance in Medicine, 80(3), 935-946. Lien externe

Z

Zaimi, A., Wabartha, M., Herman, V., Antonsanti, P.-L., Perone, C. S., & Cohen-Adad, J. (2018). AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks. Scientific Reports, 8(1), 3816 (11 pages). Disponible

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