Company Management, Scientific and Advisory Boards

Imaging publications

Santini, G., Fourcade, C., Rousseau, C., Ferrer, L., Campone, M., Colombié, M., & Rubeaux, M. (2020). Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l’apprentissage profond dans le cadre du cancer du sein métastatique. Médecine Nucléaire, 44(2), 135. https://doi.org/10.1016/j.mednuc.2020.01.085
Rubeaux, M., Joshi, N. V., Dweck, M. R., Fletcher, A., Motwani, M., Thomson, L. E., … Slomka, P. J. (2016). Motion Correction of 18F-NaF PET for Imaging Coronary Atherosclerotic Plaques. Journal of Nuclear Medicine, 57(1), 54–59. https://doi.org/10.2967/jnumed.115.162990
Santini, G., Moreau, N., & Rubeaux, M. (2019). Kidney tumor segmentation using an ensembling multi-stage deep learning approach. A contribution to the KiTS19 challenge. In Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19. University of Minnesota Libraries Publishing. https://doi.org/10.24926/548719.023
Rubeaux, M., Nunes, J.-C., Albera, L., & Garreau, M. (2011). Approximation de l’information mutuelle basée sur un développement d’edgeworth à l’ordre 3 : Application au recalage non-rigide d’images médicales.
Doris, M. K., Otaki, Y., Krishnan, S. K., Kwiecinski, J., Rubeaux, M., Alessio, A., … Slomka, P. J. (2020). Optimization of reconstruction and quantification of motion-corrected coronary PET-CT. Journal of Nuclear Cardiology, 27(2), 494–504. https://doi.org/10.1007/s12350-018-1317-5
Rubeaux, M., Nunes, J.-C., Albera, L., & Garreau, M. (2014). Medical image registration using Edgeworth-based approximation of Mutual Information. IRBM, 35(3), 139–148. https://doi.org/10.1016/j.irbm.2013.12.004
Doris, M. K., Rubeaux, M., Pawade, T., Otaki, Y., Xie, Y., Li, D., … Dey, D. (2017). Motion-Corrected Imaging of the Aortic Valve with 18 F-NaF PET/CT and PET/MRI: A Feasibility Study. Journal of Nuclear Medicine, 58(11), 1811–1814. https://doi.org/10.2967/jnumed.117.194597
Rubeaux, M., Joshi, N., Dweck, M. R., Fletcher, A., Motwani, M., Thomson, L. E., … Slomka, P. J. (2016). Demons versus level-set motion registration for coronary 18 F-sodium fluoride PET. In M. A. Styner & E. D. Angelini (Eds.) (p. 97843Y). Presented at the SPIE Medical Imaging, San Diego, California, United States. https://doi.org/10.1117/12.2217179
Rubeaux, M., Xu, Y., Germano, G., Berman, D. S., & Slomka, P. J. (2016). Normal Databases for the Relative Quantification of Myocardial Perfusion. Current Cardiovascular Imaging Reports, 9(8), 22. https://doi.org/10.1007/s12410-016-9385-x
Rubeaux, M., Doris, M. K., Alessio, A., & Slomka, P. J. (2017). Enhancing Cardiac PET by Motion Correction Techniques. Current Cardiology Reports, 19(2), 14. https://doi.org/10.1007/s11886-017-0825-2
Brodov, Y., Fish, M., Rubeaux, M., Otaki, Y., Gransar, H., Lemley, M., … Slomka, P. (2016). Quantitation of left ventricular ejection fraction reserve from early gated regadenoson stress Tc-99m high-efficiency SPECT. Journal of Nuclear Cardiology, 23(6), 1251–1261. https://doi.org/10.1007/s12350-016-0519-y
Betancur, J., Rubeaux, M., Fuchs, T. A., Otaki, Y., Arnson, Y., Slipczuk, L., … Slomka, P. J. (2017). Automatic Valve Plane Localization in Myocardial Perfusion SPECT/CT by Machine Learning: Anatomic and Clinical Validation. Journal of Nuclear Medicine, 58(6), 961–967. https://doi.org/10.2967/jnumed.116.179911
Slomka, P. J., Rubeaux, M., Le Meunier, L., Dey, D., Lazewatsky, J. L., Pan, T., … Berman, D. S. (2015). Dual-Gated Motion-Frozen Cardiac PET with Flurpiridaz F 18. Journal of Nuclear Medicine, 56(12), 1876–1881. https://doi.org/10.2967/jnumed.115.164285
Bizais, Y., Guedon, J.-P., Couturier, O., Normand, N., Devillers, A., Terve, P., … Fortineau, J. (2004). The POSITOSCOPE: an easy-to-use communicating electronic lightbox. In O. M. Ratib & H. K. Huang (Eds.) (p. 140). Presented at the Medical Imaging 2004, San Diego, CA. https://doi.org/10.1117/12.535085
Lacoeuille, F., Hindré, F., Denizot, B., Bouchet, F., Legras, P., Couturier, O., … Le Jeune, J. J. (2010). New starch-based radiotracer for lung perfusion scintigraphy. European Journal of Nuclear Medicine and Molecular Imaging, 37(1), 146–155. https://doi.org/10.1007/s00259-009-1226-6
Guédon, J., Evenou, P., Tervé, P., David, S., & Béranger, J. (2012). CEDIMS: cloud ethical DICOM image Mojette storage. In W. W. Boonn & B. J. Liu (Eds.) (p. 831907). Presented at the SPIE Medical Imaging, San Diego, California, USA. https://doi.org/10.1117/12.911396
Der Sarkissian, H., Guedon, J., Terve, P., Normand, N., & Svalbe, I. (2012). Evaluation of 3D discrete angles rotation degradations for myocardial perfusion imaging.
Didierlaurent, D., Ribes, S., Batatia, H., Jaudet, C., Dierickx, L. O., Zerdoud, S., … Courbon, F. (2012). The retrospective binning method improves the consistency of phase binning in respiratory-gated PET/CT. Physics in Medicine and Biology, 57(23), 7829–7841. https://doi.org/10.1088/0031-9155/57/23/7829
Der Sarkissian, H., Recur, B., Guedon, J., Terve, P., Normand, N., & Svalbe, I. (2013). Discrete mojette rotation on PET-CT images.
Didierlaurent, D., Jaudet, C., Ribes, S., Batatia, H., Dierickx, L. O., Zerdoud, S., … Caselles, O. (2014). Comparison of an alternative and existing binning methods to reduce the acquisition duration of 4D PET/CT: Binning methods halving the acquisition duration in 4D PET/CT. Medical Physics, 41(11), 112503. https://doi.org/10.1118/1.4897612
Grossiord, E., Talbot, H., Passat, N., Meignan, M., Terve, P., & Najman, L. (2015). Hierarchies and shape-space for pet image segmentation. In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) (pp. 1118–1121). Brooklyn, NY, USA: IEEE. https://doi.org/10.1109/ISBI.2015.7164068
Roman-Jimenez, G., Acosta, O., Leseur, J., Devillers, A., Le Gouestre, J., Ospina, J.-D., … De Crevoisier, R. (2015). Weighted quantification of 18F-FDG tumor metabolism activity using fuzzy-thresholding to predict post-treatment tumor recurrence. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2239–2242). Milan: IEEE. https://doi.org/10.1109/EMBC.2015.7318837
Roman-Jimenez, G., Crevoisier, R. D., Leseur, J., Devillers, A., Ospina, J. D., Simon, A., … Acosta, O. (2016). Detection of bladder metabolic artifacts in 18F-FDG PET imaging. Computers in Biology and Medicine, 71, 77–85. https://doi.org/10.1016/j.compbiomed.2016.02.002
de Margerie-Mellon, C., de Bazelaire, C., Montlahuc, C., Lambert, J., Martineau, A., Coulon, P., … Beigelman, C. (2016). Reducing Radiation Dose at Chest CT. Academic Radiology, 23(10), 1246–1254. https://doi.org/10.1016/j.acra.2016.05.019
Vallot, D., Caselles, O., Chaltiel, L., Fernandez, A., Gabiache, E., Dierickx, L., … Courbon, F. (2017). A clinical evaluation of the impact of the Bayesian penalized likelihood reconstruction algorithm on PET FDG metrics: Nuclear Medicine Communications, 1. https://doi.org/10.1097/MNM.0000000000000729
Grossiord, É., Passat, N., Talbot, H., Naegel, B., Kanoun, S., Tal, I., … Najman, L. (2020). Shaping for PET image analysis. Pattern Recognition Letters, 131, 307–313. https://doi.org/10.1016/j.patrec.2020.01.017