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ORCIDMichaël Sdika
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2020 – today
- 2024
[j18]Arthur Gautheron
, Michaël Sdika, Mathieu Hébert, Bruno Montcel:
An Explicit Estimated Baseline Model for Robust Estimation of Fluorophores Using Multiple-Wavelength Excitation Fluorescence Spectroscopy. IEEE Trans. Biomed. Eng. 71(1): 295-306 (2024)- [c15]Gaël Vila, Emmanuel Medernach, Inés Gonzalez Pepe, Axel Bonnet, Yohan Chatelain, Michaël Sdika, Tristan Glatard, Sorina Camarasu-Pop:
The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging. ACM-REP 2024 - [c14]Thomas Maitre, Elie Bretin, Laurent Mahieu-Williame, Michaël Sdika, Nicolas Ducros:
Hybrid Single-Pixel Camera for Dynamic Hyperspectral Imaging. ISBI 2024: 1-5 - [c13]Thomas Maitre, Elie Bretin, Romain Phan, Nicolas Ducros, Michaël Sdika:
Dynamic Single-Pixel Imaging on an Extended Field of View Without Warping the Patterns. MICCAI (7) 2024: 275-284 - 2023
- [j17]Charly Caredda, Eric Van Reeth, Laurent Mahieu-Williame, Raphaël Sablong, Michaël Sdika, Fabien C. Schneider, Thiébaud Picart, Jacques Guyotat, Bruno Montcel:
Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies. NeuroImage 278: 120286 (2023) - [j16]Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika:
A Weakly Supervised Gradient Attribution Constraint for Interpretable Classification and Anomaly Detection. IEEE Trans. Medical Imaging 42(11): 3336-3347 (2023) - [c12]Morgane Des Ligneris, Axel Bonnet, Yohan Chatelain, Tristan Glatard, Michaël Sdika, Gaël Vila, Valentine Wargnier-Dauchelle, Sorina Camarasu-Pop, Carole Frindel:
Reproducibility of Tumor Segmentation Outcomes with a Deep Learning Model. ISBI 2023: 1-5 - [c11]Slim Hachicha, Célia Le, Valentine Wargnier-Dauchelle, Michaël Sdika:
Robust Unsupervised Image to Template Registration Without Image Similarity Loss. MILLanD@MICCAI 2023: 148-157 - 2021
- [j15]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. Comput. Biol. Medicine 131: 104268 (2021) - [c10]Valentine Wargnier-Dauchelle, Thomas Grenier, Françoise Durand-Dubief, François Cotton, Michaël Sdika:
A More Interpretable Classifier For Multiple Sclerosis. ISBI 2021: 1062-1066 - 2020
- [i3]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. CoRR abs/2012.03014 (2020)
2010 – 2019
- 2019
- [j14]Clément Daviller, Thomas Grenier, Hélène Ratiney, Michaël Sdika, Pierre Croisille, Magalie Viallon:
Automatic myocardial ischemic lesion detection on magnetic resonance perfusion weighted imaging prior perfusion quantification: A pre-modeling strategy. Comput. Biol. Medicine 110: 108-119 (2019) - [j13]Clément Daviller, Thomas Grenier, Hélène Ratiney, Michaël Sdika, Pierre Croisille, Magalie Viallon:
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]. Comput. Biol. Medicine 114 (2019) - [j12]Michaël Sdika, Laure Alston, David Rousseau, Jacques Guyotat, Laurent Mahieu-Williame, Bruno Montcel:
Repetitive motion compensation for real time intraoperative video processing. Medical Image Anal. 53: 1-10 (2019) - [j11]Pierre-Antoine Ganaye, Michaël Sdika, Bill Triggs, Hugues Benoit-Cattin:
Removing segmentation inconsistencies with semi-supervised non-adjacency constraint. Medical Image Anal. 58 (2019) - [j10]Michaël Sdika:
Diffeomorphic B-spline vector fields with a tractable set of inequalities. Math. Comput. 88(320): 2827-2856 (2019) - 2018
- [j9]Charley Gros, Benjamin De Leener, Sara M. Dupont, Allan R. Martin, Michael G. Fehlings, Rohit Bakshi, Subhash Tummala, Vincent Auclair, Donald G. McLaren, Virginie Callot, Julien Cohen-Adad, Michaël Sdika:
Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Medical Image Anal. 44: 215-227 (2018) - [c9]Pierre-Antoine Ganaye, Michaël Sdika, Hugues Benoit-Cattin:
Towards integrating spatial localization in convolutional neural networks for brain image segmentation. ISBI 2018: 621-625 - [c8]Nima Hatami, Michaël Sdika, Hélène Ratiney:
Magnetic Resonance Spectroscopy Quantification Using Deep Learning. MICCAI (1) 2018: 467-475 - [c7]Pierre-Antoine Ganaye, Michaël Sdika, Hugues Benoit-Cattin:
Semi-supervised Learning for Segmentation Under Semantic Constraint. MICCAI (3) 2018: 595-602 - [i2]Pierre-Antoine Ganaye, Michaël Sdika, Hugues Benoit-Cattin:
Towards integrating spatial localization in convolutional neural networks for brain image segmentation. CoRR abs/1804.04563 (2018) - [i1]Nima Hatami, Michaël Sdika, Hélène Ratiney:
Magnetic Resonance Spectroscopy Quantification using Deep Learning. CoRR abs/1806.07237 (2018) - 2017
- [c6]Augustin Ogier, Michaël Sdika, Alexandre Foure, Arnaud Le Troter, David Bendahan:
Individual muscle segmentation in MR images: A 3D propagation through 2D non-linear registration approaches. EMBC 2017: 317-320 - [c5]Charley Gros, Benjamin De Leener, Sara M. Dupont, Allan R. Martin, Michael G. Fehlings, Rohit Bakshi, Subhash Tummala, Vincent Auclair, Donald G. McLaren, Virginie Callot, Michaël Sdika, Julien Cohen-Adad:
OptiC: Robust and Automatic Spinal Cord Localization on a Large Variety of MRI Data Using a Distance Transform Based Global Optimization. MICCAI (2) 2017: 712-719 - 2016
- [c4]Michaël Sdika, Laure Alston, Laurent Mahieu-Williame, Jacques Guyotat, David Rousseau, Bruno Montcel:
Robust real time motion compensation for intraoperative video processing during neurosurgery. ISBI 2016: 1046-1049 - 2015
- [j8]Manuel Taso, Arnaud Le Troter, Michaël Sdika, Julien Cohen-Adad, Pierre Jean Arnoux, Maxime Guye, Jean-Philippe Ranjeva, Virginie Callot:
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 117: 20-28 (2015) - [c3]Eric Van Reeth, Michaël Sdika, Pierre-Hervé Luppi, Paul-Antoine Libourel, Olivier Beuf:
Multiple labels point-set registration. ISBI 2015: 609-612 - 2014
- [j7]Vladimir S. Fonov, Arnaud Le Troter, Manuel Taso, Benjamin De Leener, G. Lévêque, M. Benhamou, Michaël Sdika, Habib Benali, Pierre-Franois Pradat, D. Louis Collins, Virginie Callot, Julien Cohen-Adad:
Framework for integrated MRI average of the spinal cord white and gray matter: The MNI-Poly-AMU template. NeuroImage 102: 817-827 (2014) - [c2]Razmig Kéchichian, Sébastien Valette, Michaël Sdika, Michel Desvignes:
Automatic 3D Multiorgan Segmentation via Clustering and Graph Cut Using Spatial Relations and Hierarchically-Registered Atlases. MCV 2014: 201-209 - 2013
- [j6]Michaël Sdika:
A Sharp Sufficient Condition for B-Spline Vector Field Invertibility. Application to Diffeomorphic Registration and Interslice Interpolation. SIAM J. Imaging Sci. 6(4): 2236-2257 (2013) - 2010
- [j5]Michaël Sdika:
Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote. Medical Image Anal. 14(2): 219-226 (2010) - [j4]SungWon Chung, Blandine Courcot, Michaël Sdika, Kristin Moffat, Caroline D. Rae, Roland G. Henry:
Bootstrap quantification of cardiac pulsation artifact in DTI. NeuroImage 49(1): 631-640 (2010)
2000 – 2009
- 2008
- [j3]SungWon Chung, Daniel Pelletier, Michaël Sdika, Ying Lu, Jeffrey I. Berman, Roland G. Henry:
Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing. NeuroImage 39(4): 1693-1705 (2008) - [j2]Michaël Sdika:
A Fast Nonrigid Image Registration With Constraints on the Jacobian Using Large Scale Constrained Optimization. IEEE Trans. Medical Imaging 27(2): 271-281 (2008) - [c1]Hélène Ratiney, Adriana Bucur, Michaël Sdika, Olivier Beuf, Franck Pilleul, Sophie Cavassila:
Effective voigt model estimation using multiple random starting values and parameter bounds settings for in vivo hepatic 1H magnetic resonance spectroscopic data. ISBI 2008: 1529-1532 - 2006
- [j1]Bill Triggs, Michaël Sdika:
Boundary conditions for Young-van Vliet recursive filtering. IEEE Trans. Signal Process. 54(6-1): 2365-2367 (2006)
Coauthor Index
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