Nombre de documents

58

Michaël Sdika


Article dans une revue21 documents

  • Michaël Sdika, Laure Alston, David Rousseau, Jacques Guyotat, Laure Mahieu-Williame, et al.. Repetitive Motion Compensation for Real Time Intraoperative Video Processing. Medical Image Analysis, Elsevier, In press. 〈hal-01974104〉
  • Charley Gros, Benjamin De Leener, Sara Dupont, Allan Martin, Michael Fehlings, et al.. Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Medical Image Analysis, Elsevier, 2018, 44, pp.215-227. 〈10.1016/j.media.2017.12.001〉. 〈hal-01690881〉
  • Michaël Sdika. Diffeomorphic B-Spline Vector Fields With a Tractable Set of Inequalities. Mathematics of Computation, American Mathematical Society, In press, 00. 〈hal-01956237〉
  • Angeline Nemeth, Lucy Di Marco, Florent Boutitie, Michael Sdika, Denis Grenier, et al.. Reproducibility of in vivo magnetic resonance imaging T 1 rho and T 2 relaxation time measurements of hip cartilage at 3.0T in healthy volunteers. Journal of Magnetic Resonance Imaging, Wiley-Blackwell, 2017, 47 (4), pp.1022-1033. 〈10.1002/jmri.25799〉. 〈hal-01560104〉
  • Michaël Sdika, Anne Tonson, Yann Le Fur, Patrick Cozzone, David Bendahan. Multi-atlas-based fully automatic segmentation of individual muscles in rat leg. Magnetic Resonance Materials in Physics, Biology and Medicine, Springer Verlag, 2016, 29 (2), pp.223-235. 〈10.1007/s10334-015-0511-6〉. 〈hal-01375862〉
  • Eric Van Reeth, Geetha Soujanya, Michaël Sdika, Frederic Cervenansky, Chueh Poh. misoSR: Medical Image Isotropic Super-Resolution Reconstruction. Midas Journal, 2015. 〈hal-01799683〉
  • Michaël Sdika. Enhancing atlas based segmentation with multiclass linear classifiers. Medical Physics, American Association of Physicists in Medicine, 2015, 42, pp.7169. 〈10.1118/1.4935946〉. 〈hal-01375850〉
  • Manuel Taso, Arnaud Le Troter, Michaël Sdika, Julien Cohen-Adad, Pierre-Jean Arnoux, et al.. A reliable spatially normalized template of the human spinal cord - Applications to automated white matter/gray matter segmentation and tensor-based morphometry (TBM) mapping of gray matter alterations occurring with age. NeuroImage, Elsevier, 2015, 117, p.20-28. 〈10.1016/j.neuroimage.2015.05.034〉. 〈hal-01414352〉
  • D. Merhej, H. Ratiney, C. Diab, M. Khalil, Michaël Sdika, et al.. Fast multidimensional NMR spectroscopy for sparse spectra. NMR in Biomedicine, Wiley, 2014, 27 (6), pp.640-655. 〈10.1002/nbm.3100〉. 〈hal-00977517〉
  • V.S. Fonov, A. Le Troter, M. Taso, B. De Leener, G. Lévêque, et al.. Framework for integrated MRI average of the spinal cord white and gray matter: The MNI–Poly–AMU template. NeuroImage, Elsevier, 2014, 102 (Pt2), pp.817-827. 〈10.1016/j.neuroimage.2014.08.057〉. 〈hal-01117512〉
  • Michaël Sdika. A Sharp Sufficient Condition for B-Spline Vector Field Invertibility. Application to Diffeomorphic Registration and Interslice Interpolation.. SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2013, 6 (4), pp.2236-2257. 〈10.1137/120879920〉. 〈hal-01902498〉
  • P.A. Gourraud, Michaël Sdika, P. Khankhanian, R.G. Henry, A. Beheshtian, et al.. A genome-wide association study of brain lesion distribution in multiple sclerosis.. Brain, 2013, 136, pp.1012-24. 〈10.1093/brain/aws363〉. 〈hal-01902499〉
  • M Taso, A Le Troter, M Sdika, Jean-Philippe Ranjeva, M Guye, et al.. Construction of an in vivo human spinal cord atlas based on high-resolution MR images at cervical and thoracic levels: preliminary results. Magnetic Resonance Materials in Physics, Biology and Medicine, Springer Verlag, 2013, 27, pp.257-267. 〈hal-01097040〉
  • Michaël Sdika. Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote. Med Image Anal, Elsevier, 2010, 14 (2), pp.219-26. 〈hal-00617791〉
  • S. Chung, B. Courcot, Michaël Sdika, K. Moffat, C. Rae, et al.. Bootstrap quantification of cardiac pulsation artifact in DTI. NeuroImage, Elsevier, 2010, 49 (1), pp.631-40. 〈hal-00617749〉
  • Michaël Sdika, Daniel Pelletier. Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping.. Human Brain Mapping, Wiley, 2009, 30, pp.1060-7. 〈10.1002/hbm.20566〉. 〈hal-01902507〉
  • Michaël Sdika, D. Pelletier. Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping.. Hum Brain Mapp, 2009, 30, pp.1060-7. 〈10.1002/hbm.20566〉. 〈hal-01902506〉
  • S. Chung, D. Pelletier, Michaël Sdika, Y. Lu, I. Berman, et al.. Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing.. NeuroImage, Elsevier, 2008, 39, pp.1693-705. 〈10.1016/j.neuroimage.2007.10.039〉. 〈hal-01902508〉
  • H. Ratiney, S. M. Noworolski, Michaël Sdika, R. Srinivasan, R. G. Henry, et al.. Estimation of metabolite T1 relaxation times using tissue specific analysis, signal averaging and bootstrapping from magnetic resonance spectroscopic imaging data. Magn Reson Mater Phy Biol Med, 2007, 20 (3), pp.143-155. 〈hal-00443421〉
  • Bill Triggs, Michaël Sdika. Boundary conditions for Young - van Vliet recursive filtering. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2006, 54 (6), pp.2365 - 2367. 〈http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1634831〉. 〈10.1109/TSP.2006.871980〉. 〈inria-00548616〉
  • H. Ratiney, Michaël Sdika, Y. Coenradie, S. Cavassila, D. Van Ormondt, et al.. Time-Domain Semi-Parametric Estimation Based on a Metabolite Basis Set. Nuclear Magnetic Resonance in Biomedicine, 2005, 18, pp.1-13. 〈hal-00443422〉

Communication dans un congrès35 documents

  • Pierre-Antoine Ganaye, Michael Sdika, Hugues Benoit-Cattin. Towards Integrating Spatial Localization in Convolutional Neural Networks for Brain Image Segmentation. 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Apr 2018, Washington, United States. IEEE, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 〈10.1109/ISBI.2018.8363652〉. 〈hal-01812045〉
  • Benjamin Leporq, Amine Bouhamama, Fabrice Lame, Catherine Bihane, Michael Sdika, et al.. MRI-based radiomic to assess lipomatous soft tissue tumors malignancy: a pilot study. International Society of Magnetic Resonance in Medicine and European Society of Magnetic Resonance in Medicine and Biology joint Annual Meeting, Jun 2018, Paris, France. 〈hal-01921659〉
  • C. Caredda, L. Mahieu-Williame, R Sablong, Michaël Sdika, L.M. Alston, et al.. Neuroimagerie fonctionnelle multispectrale. OPTDIAG, 2018, Paris, Unknown Region. 2018. 〈hal-01902495〉
  • Pierre-Antoine Ganaye, Michaël Sdika, Hugues Benoit-Cattin. Semi-supervised learning for segmentation under semantic constraint. MICCAI, Sep 2018, Grenada, Spain. 〈https://www.miccai2018.org/en/〉. 〈hal-01904641〉
  • Nima Hatami, Michaël Sdika, Hélène Ratiney. Towards handling artefacts in Convolutional Neural Networks-based MRS quantification. ISMRM MRS Workshop, Oct 2018, Utrecht, Netherlands. 〈https://mrsworkshop2018.org/〉. 〈hal-01904680〉
  • Nima Hatami, Michaël Sdika, Hélène Ratiney. Magnetic Resonance Spectroscopy Quantification using Deep Learning. MICCAI, Oct 2018, Grenada, Spain. 〈hal-01904617〉
  • Augustin Ogier, Michael Sdika, Alexandre Foure, Arnaud Le Troter, David Bendahan. Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jul 2017, Seogwipo, South Korea. 2017, pp.317--320, 2017, 〈10.1109/EMBC.2017.8036826〉. 〈hal-01657939〉
  • Charley Gros, Benjamin De Leener, Sara Dupont, Allan R. Martin, Michael G. Fehlings, et al.. OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization. Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017, Sep 2017, Québec, Canada. 10434, pp.712-719, 2017, Lecture Notes in Computer Science book series. 〈10.1007/978-3-319-66185-8_80〉. 〈hal-01713965〉
  • Michaël Sdika, V. Callot. Automatic Detection of the Spinal Cord Centerline using Machine Learning and Global Nonlinear Optimization. Recherche en Imagerie et Technologies pour la Santé - RITS 2017, Mar 2017, Lyon, France. 2017. 〈hal-01721389〉
  • A. Ogier, Michaël Sdika, A. Fouré, A. Le Troter, D. Bendahan. Segmentation des muscles individuels en IRM basée sur des approches de recalage non-linéaire. 3ème Congrès de la SFRMBM, Mar 2017, Bordeaux, France. 〈hal-01560300〉
  • Michaël Sdika, Laure Alston, Laurent Mahieu-Williame, Jacques Guyotat, David Rousseau, et al.. Robust real time motion compensation for intraoperative video processing during neurosurgery. IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016), Apr 2016, Prague, Czech Republic. Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on. 〈10.1109/ISBI.2016.7493445〉. 〈hal-01451713〉
  • Angéline Nemeth, Lucy Di Marco, Denis Grenier, Michaël Sdika, Olivier Beuf, et al.. Repeatability and reproducibility of in vivo magnetic resonance T1rho relaxation time measurements of hip cartilage at 3T. ISMRM 2016, May 2016, Singapour, Singapore. pp.Abstract #4490. 〈hal-01434177〉
  • Eric Van Reeth, Michaël Sdika, Sophie Gaillard, Pierre-Hervé Luppi, Paul-Antoine Libourel, et al.. Amélioration de résolution spatiale et SNR d’images cérébrales pondérées T2 de rat : application de la super-résolution. 2ème Congrès de la SFRMBM, Mar 2015, Grenoble, France. 〈hal-01288527〉
  • E. Van Reeth, Michaël Sdika, S. Gaillard, P.-H. Luppi, P.-A. Libourel, et al.. Improving the spatial resolution and SNR of rat brain T2-weighted MR images: application of a super-resolution method. ISMRM 23rd Annual Meeting & Exhibition, May 2015, Toronto, Canada. 〈hal-01288505〉
  • E. Van Reeth, M Sdika, P.-H. Luppi, P.-A. Libourel, O. Beuf. Multiple labels point-set registration. 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), Apr 2015, New-York, United States. pp.609 - 612, Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on. 〈10.1109/ISBI.2015.7163947〉. 〈hal-01272177〉
  • E. Van Reeth, Michaël Sdika, S. Gaillard, P.-H. Luppi, P.-A. Libourel, et al.. Amélioration de résolution spatiale et SNR d\textquoterightimages cérébrales pondérées T2 de rat : application de la super-résolution. SFRMBM, 2015, Grenoble, France. 2015. 〈hal-01902496〉
  • M. Benhamou, V.S. Fonov, M. Taso, A. Le Troter, Michaël Sdika, et al.. Atlas of White-Matter Tracts in the Human Spinal Cord. ISMRM-ESMRMB Annual Meeting 2014, May 2014, Milan, Italy. 〈hal-01117699〉
  • V.S. Fonov, A. Le Troter, M. Taso, G. Leveque, M. Benhamou, et al.. MNI-Poly-AMU Average Anatomical Template for Automatic Spinal Cord Measurements. ISMRM-ESMRMB Annual Meeting 2014, May 2014, Milan, Italy. 2014. 〈hal-01117634〉
  • M. Taso, A. Le Troter, Michaël Sdika, V.S. Fonov, J. Cohen-Adad, et al.. Validation of a 2D Spinal Cord Probabilistic Atlas. Application to FA Measurement and VBM Study of the GM Atrophy Occurring with Age. ISMRM-ESMRMB Annual Meeting 2014, May 2014, Milan, France. 2014. 〈hal-01117689〉
  • C. Frindel, H. Rositi, Michaël Sdika, F. Chauveau, T.-H. Cho, et al.. Démonstrateur en imagerie à vocation diagnostique dans le cadre de l'AVC. 4èmes Journées Démonstrateurs 2013, Jun 2013, Angers, France. 〈hal-00849981〉
  • Benjamin Leporq, Franck Pilleul, Jérôme Dumortier, Olivier Guillaud, Thibaud Lefort, et al.. Liver perfusion quantification with MR-DCE imaging at 3.0 T for liver fibrosis assessment in patients with chronic liver diseases. ISMRM 21st Annual Meeting & Exhibition, Apr 2013, Salt-Lake City, United States. pp.3911, 2013, 2013 Annual ISMRM Meeting Proceedings. 〈hal-01128036〉
  • C Frindel, H. Rositi, Michaël Sdika, F. Chauveau, T.H. Cho, et al.. Démonstrateur en imagerie à vocation diagnostique dans le cadre de l\textquoterightAVC. 4ème Journée Démonstrateurs, 2013, Angers, France. 2013. 〈hal-01902497〉
  • H. Ratiney, Michaël Sdika, O. Beuf, Y. Le Fur, S. Cavassila. Towards a biochemical and structure specific quantitative analysis of the mouse brain using Magnetic Resonance Spectroscopic Imaging at 11.7T. Journées Thématiques GDR "Imagerie in vivo" (IMAGIV), 2011, Paris, Unknown Region. 2011. 〈hal-01879479〉
  • G Duhamel, T. Marqueste, Michaël Sdika, M. Tachrount, P. Decherchi, et al.. Vascular Alterations and Recruitment in Spinal Cord Injury Revealed by Multislice Arterial Spin Labeling (ASL) Perfusion Imaging. ISMRM-ESMRMB Joint Annual Meeting, 2011, Stockholm, Sweden. pp.5092, 2011. 〈hal-01902500〉
  • Michaël Sdika, Y. Le Fur, P. . Cozzone. Optimal Recombination of Multi-Coils CSI Data using Image Based Sensitivity Map. 20th Annual meeting of the ISMRM, 2011, Montreal, Canada. pp.3478, 2011. 〈hal-01902502〉
  • Michaël Sdika, A. Tonson, P. . Cozzone, D. Bendahan. Multi Atlas Segmentation of Rat Leg Muscles. 20th Annual meeting of the ISMRM, 2011, Montreal, Canada. pp.2562, 2011. 〈hal-01902503〉
  • H. Ratiney, Y. Le Fur, Michaël Sdika, S. Cavassila. Short Echo Time H1 Chemical Shift Imaging data quantification in the mouse brain at 11.7T using a constrained parametric macromolecular model. ISMRM-ESMRMB Joint Annual Meeting, 2010, Stockholm, Sweden. 2010. 〈hal-01879492〉
  • Michaël Sdika, V. Callot, M Hebert, G Duhamel, P.J. Cozzone. Segmentation of the Structure of the Mouse Spinal Cord on DTI images. ISMRM-ESMRMB Joint Annual Meeting, 2010, Stockholm, Sweden. pp.5115, 2010. 〈hal-01902504〉
  • Michaël Sdika, V. Callot, M Hebert, G Duhamel, P.J. Cozzone. A Fully Automated White Matter/Gray Matter Segmentation of Mice Spinal Cord on DTI Images. ISMRM-ESMRMB Joint Annual Meeting, 2010, Stockholm, Sweden. pp.442, 2010. 〈hal-01902505〉
  • H. Ratiney, Michaël Sdika, O. Beuf, Y. Le Fur, S. Cavassila. Towards structure specific macromolecular content of mouse brain from Chemical Shift Imaging data at 11.7T. ISMRM, 2009, Hawai, USA, Unknown Region. pp.3293, 2009. 〈hal-01879496〉
  • H. Ratiney, Y. Le Fur, Michaël Sdika, M. Touret, A. Bernard, et al.. Quantitative assessment of the brain macromolecular content in a mouse model of neuro-inflammation from chemical shift imaging data at 11.7T. ESMRMB, 2009, Antalya, Turkey. pp.39, 2009. 〈hal-01879500〉
  • H. Ratiney, A. Bucur, Michaël Sdika, O. Beuf, F. Pilleul, et al.. Effective Voigt model estimation using multiple random starting values and parameter bounds settings for in vivo hepatic 1H Magnetic Resonance Spectroscopy data. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008, Paris, France. pp.1529-1532, 2008, 〈10.1109/ISBI.2008.4541300〉. 〈hal-01879508〉
  • H. Ratiney, S.M. Noworolski, Michaël Sdika, R. Srinivasan, R.G. Henry, et al.. Regional Estimation of T1 Metabolite Relaxation using 2D MRSI and a Bootstrap Approach at 1.5T. Int. Soc. Magnetic Resonance in Medicine, 14th Scientific Meeting and Exhibition, 2006, Seattle, Washington, USA, Unknown Region. 2006. 〈hal-01879435〉
  • H. Ratiney, E. Capobianco, Michaël Sdika, H. Rabeson, C. Cudalbu, et al.. Semi-Parametric estimation in In vivo MR Spectroscopy. ProRISC, IEEE Benelux, 2005, Veldhoven, The, Netherlands. pp.658-667, 2005. 〈hal-01879442〉
  • Matthijs Douze, Michaël Sdika, Cordelia Schmid. PhotoMole: retrieval from a database of natural images. CVPR'05 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Jun 2005, San Diego, United States. IEEE, pp.1-4, 2005. 〈hal-01902510〉

Direction d'ouvrage, Proceedings, Dossier1 document

  • H. Ratiney, A. Bucur, Michaël Sdika, O. Beuf, F. Pilleul, et al.. Effective Voigt model estimation using multiple random starting values and parameter bounds settings for in vivo hepatic 1H Magnetic Resonance Spectroscopy data.. pp.1529-1532, 2008. 〈hal-01879505〉

Autre publication1 document

  • Charles Raux, Michaël Sdika, Vincent Hermemier. Simulation de la dynamique du système de déplacements urbains : une plate-forme de modélisation. Rapport de recherche. 2003. 〈halshs-00093625〉