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Alonso Ortiz, E., Gros, C., Foias, A., Abramovic, M., Ameitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Buchel, C., Budde, M., Callot, V., De Leener, B., Descoteaux, M., De Sousa, P. L., Dostal, M., Doyon, J., Dvorak, A., ... Cohen-Adad, J. (août 2020). Quantitative MRI of the spinal cord : reproducibility and normative values across 40 sites [Communication écrite]. ISMRM & SMRT annual Meeting & Exhibition (ISMRM 2020). Lien externe
Cohen-Adad, J., Alonso Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J. E., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., ... Xu, J. (2021). Generic acquisition protocol for quantitative MRI of the spinal cord. Nature Protocols, 16(10), 4611-4632. Disponible
Cohen-Adad, J., Alonso Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R., Barth, M., Battiston, M., Büchel, C., Budde, M. D., Callot, V., Combes, A. J.E., De Leener, B., Descoteaux, M., Sousa, P. L. , Dostál, M., Doyon, J., Dvorak, A., ... Xu, J. (2021). Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific Data, 8(1), 251 (2 pages). Disponible
Cohen-Adad, J., Alonso Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J. E., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., ... Xu, J. (2021). Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers (vol 8, 219, 2021). Scientific Data, 8(1), 242 (1 page). Disponible
Cohen-Adad, J., Alonso Ortiz, E., Abramovic, M., Arneitz, C., Atcheson, N., Barlow, L., Barry, R. L., Barth, M., Battiston, M., Büchel, C., Budde, M., Callot, V., Combes, A. J. E., De Leener, B., Descoteaux, M., de Sousa, P. L., Dostál, M., Doyon, J., Dvorak, A., ... Xu, J. (2021). Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers. Scientific Data, 8(1), 219 (17 pages). Disponible
Eden, D., Gros, C., Badji, A., Dupont, S. M., De Leener, B., Maranzano, J., Zhuoquiong, R., Liu, Y., Granberg, T., Ouellette, R., Stawiarz, L., Hillert, J., Talbott, J., Bannier, É., Kerbrat, A., Edan, G., Labauge, P., Callot, V., Pelletier, J., ... Cohen-Adad, J. (2019). Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain, 142(3), 633-646. Lien externe
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
Gros, C., De Leener, B., Badji, A., Maranzano, J., Eden, D., Dupont, S. M., Talbott, J., Zhuoquiong, R., Liu, Y., Granberg, T., Ouellette, R., Tachibana, Y., Hori, M., Kamiya, K., Chougar, L., Stawiarz, L., Hillert, J., Bannier, É., Kerbrat, A., ... Cohen-Adad, J. (2019). Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. NeuroImage, 184, 901-915. Lien externe
Lemay, A., Gros, C., Zhuo, Z., Zhang, J., Duan, Y., Cohen-Adad, J., & Liu, Y. (2021). Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning. NeuroImage - Clinical, 31, 9 pages. Disponible
Lemay, A., Gros, C., Vincent, O., Liu, Y., Cohen, J. P., & Cohen-Adad, J. (juillet 2021). Benefits of linear conditioning for segmentation using metadata [Communication écrite]. 4th Conference on Medical Imaging with Deep Learning (CMDL 2021), Lubeck, Germany. Lien externe
Lemay, A., Gros, C., Vincent, O., Liu, Y., Cohen, J. P., & Cohen-Adad, J. (juillet 2021). Benefits of Linear Conditioning with Metadata for Image Segmentation [Présentation]. Dans 4th Conference on Medical Imaging with Deep Learning (MIDL 2021). Publié dans Proceedings of Machine Learning Research, 143. Lien externe
