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Michaël Sdika

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  • Pierre-Antoine Ganaye, Michaël Sdika, Bill Triggs, Hugues Benoit-Cattin. Removing Segmentation Inconsistencies with Semi-Supervised Non-Adjacency Constraint. Medical Image Analysis, Elsevier, 2019, 58, pp.101551. ⟨10.1016/j.media.2019.101551⟩. ⟨hal-02275956⟩
  • Michaël Sdika. Diffeomorphic B-Spline Vector Fields With a Tractable Set of Inequalities. Mathematics of Computation, American Mathematical Society, 2019, 88 (320), pp.2827--2856. ⟨10.1090/mcom/3419⟩. ⟨hal-01956237⟩
  • Michaël Sdika, Laure Alston, David Rousseau, Jacques Guyotat, Laurent Mahieu-Williame, et al.. Repetitive Motion Compensation for Real Time Intraoperative Video Processing. Medical Image Analysis, Elsevier, 2019, 53, pp.1-10. ⟨10.1016/j.media.2018.12.005⟩. ⟨hal-01974104v2⟩
  • Charley Gros,  ..... Michaël Sdika, . 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⟩

 

 

Journal articles28 documents

  • Matthieu Martin, Bruno Sciolla, Michaël Sdika, Philippe Quetin, Philippe Delachartre. Automatic Segmentation and Location Learning of Neonatal Cerebral Ventricles in 3D Ultrasound Data Combining CNN and CPPN. Computers in Biology and Medicine, Elsevier, 2021, pp.104268. ⟨10.1016/j.compbiomed.2021.104268⟩. ⟨hal-03148181⟩
  • Benjamin Leporq, Amine Bouhamama, Frank Pilleul, Fabrice Lame, Catherine Bihane, et al.. MRI-based radiomics to predict lipomatous soft tissue tumors malignancy: a pilot study. Cancer Imaging, BMC, 2020, 20 (1), pp.Article number: 78. ⟨10.1186/s40644-020-00354-7⟩. ⟨hal-03107185⟩
  • Charly Caredda, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Jacques Guyotat, et al.. Optimal Spectral Combination of a Hyperspectral Camera for Intraoperative Hemodynamic and Metabolic Brain Mapping. Applied Sciences, MDPI, 2020, 10 (15), pp.5158. ⟨10.3390/app10155158⟩. ⟨hal-02908361⟩
  • Clément Daviller, Thomas Grenier, Hélène Ratiney, Michaël Sdika, Pierre Croisille, et al.. Corrigendum to “Automatic myocardial ischemic lesion detection on magnetic resonance perfusion weighted imaging prior perfusion quantification: A pre-modeling strategy” [Comput. Biol. Med. 110 (2019) 108–119]. Computers in Biology and Medicine, Elsevier, 2019, 114, pp.103455. ⟨10.1016/j.compbiomed.2019.103455⟩. ⟨hal-03009072⟩
  • Clément Daviller, Thomas Grenier, Hélène Ratiney, Michaël Sdika, Pierre Croisille, et al.. Automatic myocardial ischemic lesion detection on magnetic resonance perfusion weighted imaging prior perfusion quantification: A pre-modeling strategy. Computers in Biology and Medicine, Elsevier, 2019, 110, pp.108-119. ⟨10.1016/j.compbiomed.2019.05.001⟩. ⟨hal-02135018⟩
  • Michaël Sdika, Laure Alston, David Rousseau, Jacques Guyotat, Laurent Mahieu-Williame, et al.. Repetitive Motion Compensation for Real Time Intraoperative Video Processing. Medical Image Analysis, Elsevier, 2019, 53, pp.1-10. ⟨10.1016/j.media.2018.12.005⟩. ⟨hal-01974104v2⟩
  • Michaël Sdika. Diffeomorphic B-Spline Vector Fields With a Tractable Set of Inequalities. Mathematics of Computation, American Mathematical Society, 2019, 88 (320), pp.2827--2856. ⟨10.1090/mcom/3419⟩. ⟨hal-01956237⟩
  • Charly Caredda, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Laure Alston, et al.. Intraoperative quantitative functional brain mapping using an RGB camera. Neurophotonics, Society of Photo-optical Instrumentation Engineers (SPIE), 2019, 6 (04), pp.1. ⟨10.1117/1.NPh.6.4.045015⟩. ⟨hal-02425832⟩
  • Pierre-Antoine Ganaye, Michaël Sdika, Bill Triggs, Hugues Benoit-Cattin. Removing Segmentation Inconsistencies with Semi-Supervised Non-Adjacency Constraint. Medical Image Analysis, Elsevier, 2019, 58, pp.101551. ⟨10.1016/j.media.2019.101551⟩. ⟨hal-02275956⟩
  • 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⟩
  • 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 J 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, Gaëtan 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 - A Journal of Neurology , Oxford University Press (OUP), 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⟩
  • 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. Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote. Medical Image Analysis, Elsevier, 2010, 14 (2), pp.219-26. ⟨10.1016/j.media.2009.12.004⟩. ⟨hal-00617791⟩
  • 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⟩
  • 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⟩
  • Michaël Sdika. A Fast Nonrigid Image Registration With Constraints on the Jacobian Using Large Scale Constrained Optimization. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2008, 27 (2), pp.271-281. ⟨10.1109/TMI.2007.905820⟩. ⟨hal-02073305⟩
  • 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. ⟨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⟩

Conference papers41 documents

  • Arthur Gautheron, Michaël Sdika, Mathieu Hébert, Bruno Montcel. Robust Estimation of 5-ALA Induced PpIX Multiple-Wavelength Excitation Fluorescence Spectroscopy for Improving Glioma Classification. Spie Photonics Europe, Apr 2022, Strasbourg, France. ⟨hal-03665499⟩
  • Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika. Un Classifieur plus Interprétable pour la SEP. Congrès Société Française de Résonance Magnétique en Biologie et Médecine (SFRMBM), Sep 2021, Lyon, France. ⟨hal-03212961⟩
  • Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika. A More Interpretable Classifier for Multiple Sclerosis. International Symposium on Biomedical Imaging (ISBI), Apr 2021, Nice, France. ⟨10.1109/ISBI48211.2021.9434074⟩. ⟨hal-03212945⟩
  • Huawei Liu, Emilie Xie, H. Ratiney, Michaël Sdika, Yan Li. Application of Deep Leaning Model for Quality Control of Short-echo 7T MRSI with Various Disease Types. 2021 ISMRM & SMRT Annual Meeting, May 2021, virtual Vancouver, Canada. ⟨hal-03519714⟩
  • Charly Caredda, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Jacques Guyotat, et al.. Intraoperative functional and metabolic brain mapping using hyperspectral imaging. Photonic west, Feb 2020, San Francisco, United States. pp.11, ⟨10.1117/12.2545968⟩. ⟨hal-02539551⟩
  • Nima Hatami, Hélène Ratiney, Michaël Sdika. MR SPECTROSCOPY ARTIFACT REMOVAL WITH U-NET CONVOLUTIONAL NEURAL NETWORK. 27th Annual meeting of the ISMRM, May 2019, Montreal, Canada. ⟨hal-02129946⟩
  • Benjamin Leporq, Amine Bouhamama, Fabrice Lame, Catherine Bihane, Michaël Sdika, et al.. MRI-based radiomic to predict lipomatous soft tissue tumors malignancy. 27th Annual meeting of the ISMRM, May 2019, Montréal, Canada. ⟨hal-02266792⟩
  • Charly Caredda, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Bruno Montcel. Pixel-wise modied Beer-Lambert model for intraoperative functional brain mapping. European Conferences on Biomedical Optics, Jun 2019, Munich, Germany. ⟨hal-02142540⟩
  • Matthieu Martin, Bruno Sciolla, Michaël Sdika, Philippe Quetin, Philippe Delachartre. Segmentation of neonates cerebral ventricles with 2D CNN in 3D US data: suitable training-set size and data augmentation strategies. 2019 IEEE International Ultrasonics Symposium (IUS), Oct 2019, Glasgow, United Kingdom. pp.2122-2125, ⟨10.1109/ULTSYM.2019.8925799⟩. ⟨hal-03148378⟩
  • 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. ⟨10.1109/ISBI.2018.8363652⟩. ⟨hal-01812045⟩
  • Nima Hatami, Michaël Sdika, Hélène Ratiney. Towards handling artefacts in Convolutional Neural Networks-based MRS quantification. ISMRM MRS Workshop, Oct 2018, Utrecht, Netherlands. ⟨hal-01904680⟩
  • Nima Hatami, Michaël Sdika, Hélène Ratiney. Magnetic Resonance Spectroscopy Quantification using Deep Learning. MICCAI, Oct 2018, Grenada, Spain. ⟨hal-01904617⟩
  • Matthieu Martin, Bruno Sciolla, Michaël Sdika, Xiaoyu Wang, Philippe Quétin, et al.. Automatic Segmentation of the Cerebral Ventricle in Neonates Using Deep Learning with 3D Reconstructed Freehand Ultrasound Imaging. 2018 IEEE International Ultrasonics Symposium (IUS), Oct 2018, Kobe, France. pp.1-4. ⟨hal-02043054⟩
  • Pierre-Antoine Ganaye, Michaël Sdika, Hugues Benoit-Cattin. Semi-supervised learning for segmentation under semantic constraint. MICCAI, Sep 2018, Grenada, Spain. ⟨hal-01904641⟩
  • C. Caredda, L. Mahieu-Williame, R Sablong, Michaël Sdika, L.M. Alston, et al.. Neuroimagerie fonctionnelle multispectrale. OPTDIAG, 2018, Paris, Unknown Region. ⟨hal-01902495⟩
  • 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⟩
  • 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. ⟨hal-01721389⟩
  • Augustin C. 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. The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC’17), Jul 2017, Seogwipo, South Korea. pp.317--320, ⟨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. pp.712-719, ⟨10.1007/978-3-319-66185-8_80⟩. ⟨hal-01713965⟩
  • 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. ⟨10.1109/ISBI.2016.7493445⟩. ⟨hal-01451713⟩
  • 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, ⟨10.1109/ISBI.2015.7163947⟩. ⟨hal-01272177⟩
  • 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, Gaëtan Lévêque, M. Benhamou, et al.. MNI-Poly-AMU Average Anatomical Template for Automatic Spinal Cord Measurements. ISMRM-ESMRMB Annual Meeting 2014, May 2014, Milan, Italy. ⟨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. ⟨hal-01117689⟩
  • 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. ⟨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'AVC. 4èmes Journées Démonstrateurs 2013, Jun 2013, Angers, France. ⟨hal-00849981⟩
  • 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. ⟨hal-01902503⟩
  • 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. ⟨hal-01902502⟩
  • 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. ⟨hal-01879479⟩
  • Guillaume Duhamel, Tanguy 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. ⟨hal-01902500⟩
  • 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. ⟨hal-01879492⟩
  • Michaël Sdika, V. Callot, M Hebert, Guillaume 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. ⟨hal-01902504⟩
  • Michaël Sdika, V. Callot, M Hebert, Guillaume 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. ⟨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, United States. pp.3293. ⟨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. ⟨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, ⟨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. ⟨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. ⟨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. pp.1-4. ⟨hal-01902510⟩

Poster communications10 documents

  • Anne Josset, C. Caredda, Eric van Reeth, L. Mahieu-Williame, Raphaël Sablong, et al.. Comparison of intraoperative functional brain map obtained with RGB imaging with preoperative functional brain map obtained with functional magnetic Resonance imaging. fNIRS 2021, Oct 2021, London, United Kingdom. ⟨hal-03420561⟩
  • C. Caredda, L. Mahieu-Williame, R. Sablong, M Sdika, J. Guyotat, et al.. Intraoperative functional brain mapping based on RGB imaging. fNIRS UK, Sep 2019, Birmingham, United Kingdom. ⟨hal-02894964⟩
  • C. Caredda, L. Mahieu-Williame, R. Sablong, M Sdika, J. Guyotat, et al.. Real time intraoperative functional brain mapping using a RGB camera. Colloque RITS, May 2019, Tours, France. ⟨hal-02142491⟩
  • C. Caredda, L. Mahieu-Williame, R. Sablong, M Sdika, L. Alston, et al.. Neuroimagerie fonctionnelle multispectrale interventionnelle. OptDiag 2018, May 2018, Paris, France. ⟨hal-02894966⟩
  • Benjamin Leporq, Amine Bouhamama, F. Lame, Catherine Bihane, Michaël Sdika, et al.. MRI-Based Radiomic to Assess Lipomatous Soft Tissue Tumors Malignancy: A Pilot Study. Forum de la recherche en Cancérologie 2018, Apr 2018, Villeurbanne, France. ⟨hal-01990614⟩
  • Augustin C. Ogier, Alexandre Fouré, Michaël Sdika, Arnaud Le Troter, David Bendahan. Segmentation d’images IRM à 7T des muscles individuels basée sur des approches de propagation de masques. 15es Journées de la Société Française de Myologie (JSFM), Nov 2017, Colmar, France. ⟨hal-02000426⟩
  • Augustin C. Ogier, Alexandre Fouré, Michaël Sdika, Arnaud Le Troter, David Bendahan. 3D MRI Segmentation of muscle through 2D multi-label propagation at 7T. The 34th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology (ESMRMB), Oct 2017, Barcelone, Spain. ⟨hal-02000610⟩
  • Augustin C. Ogier, Alexandre Fouré, Michaël Sdika, Arnaud Le Troter, David Bendahan. An accurate supervised segmentation of 3D individual lower leg muscles from 7T-MRI using label propagation. MYO-MRI, Imaging in Neuromuscular Disease, Nov 2017, Berlin, Germany. ⟨hal-02000564⟩
  • Augustin C. Ogier, Michaël Sdika, Alexandre Fouré, Arnaud Le Troter, David Bendahan. Segmentation des muscles individuels en IRM basée sur des approches de recalage non-linéaire. 3ème Congrès de la Société Française de Résonance Magnétique en Biologie et Médecine (SFRMBM), Mar 2017, Bordeaux, France. ⟨hal-01560300⟩
  • 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⟩

Other publications1 document

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