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1. Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

Author

Snoussi, Haykel, Cohen-Adad, Julien, Combes, Benoit, Bannier, Elise, Tounekti, Slimane, Kerbrat, Anne, Barillot, Christian, and Caruyer, Emmanuel

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics
Abstract

Multiple sclerosis is an inflammatory disorder of the central nervous system. Quantitative MRI has huge potential to provide intrinsic and normative values of tissue properties useful for diagnosis, prognosis and ultimately clinical follow-up of this disease. However, there is a large discrepancy between the clinical observations and how the pathology is exhibited in MRI brain scans. Complementary to brain imaging, the study of multiple sclerosis lesions in the spinal cord has recently gained interest as a potential marker for early physical impairment. Therefore, investigating how the spinal cord is damaged using quantitative imaging, in particular, diffusion MRI, becomes an acute challenge. In this work, we extract average diffusion MRI metrics per vertebral level from spinal cord data acquired from multiple clinical sites. The diffusion-based metrics involved are extracted from the diffusion tensor imaging and Ball-and-Stick models and quantified for every cervical vertebral level using a collection of image processing methods and an atlas-based approach. Then, we perform a statistical analysis study to characterize the feasibility of these metrics to detect lesions. Specifically, we study the usefulness of combining different metrics to improve the accuracy prediction score associated with the presence of multiple sclerosis lesions. We demonstrate the grade of sensitivity to underlying microstructure changes in MS patients of each metric. Ball-and-Stick provides novel information about the MS damage to tissue microstructure. In addition, we show that choosing a subset of metrics: [FA, RD, MD] and [FWW, MD, Stick-AD, RD], which bring complementary information, has significantly increased the prediction score of the presence of the MS lesion in the cervical spinal cord.

Published
2021
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2. Evaluation of distortion correction methods in diffusion MRI of the spinal cord

Author

Snoussi, Haykel, Cohen-Adad, Julien, Commowick, Olivier, Combes, Benoit, Bannier, Elise, Leguy, Soizic, Kerbrat, Anne, Barillot, Christian, and Caruyer, Emmanuel

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics
Abstract

Background: Magnetic field inhomogeneities generate important geometric distortions in reconstructed echo-planar images. Various procedures were proposed for correcting these distortions on brain images; yet, few neuroimaging studies tailored and incorporated the use of these techniques in spinal cord diffusion MRI. Purpose: We present a comparative evaluation of distortion correction methods that use the reversed gradient polarity technique on spinal cord. We propose novel geometric metrics to measure the alignment of the reconstructed diffusion model with the apparent centerline of the spinal cord. Subjects: 95 subjects, among which 29 healthy controls and 66 multiple sclerosis patients. Assessment: Geometric distortions were corrected using 4 state-of-the-art methods. We measured the alignment of the principal direction of diffusion with the apparent centerline of the spine after correction and the correlation with the reference anatomical image. Results are computed per vertebral level, to evaluate the impact on different portions of the spine. Besides, subjective evaluation of the quality of the correction of healthy subjects images was performed by three expert raters. Results: As a result of distortion correction, the diffusion directions are better aligned locally with the centerline, in particular at both ends of the acquisition window. The cross-correlation with anatomical image is also improved by Hyperelastic Susceptibility Artefact Correction (HySCO) and block-matching. The subjective evaluation for HySCO is significantly better (p < 0.05) than for Block-Matching; TOPUP performs significantly worse than the three other methods. Conclusion: Correction based on HySCO provide best results among the selected methods.

Published
2021

3. Reproducibility and Evolution of Diffusion MRI Measurements within the Cervical Spinal Cord in Multiple Sclerosis

Author

Snoussi, Haykel, Caruyer, Emmanuel, Combes, Benoit, Commowick, Olivier, Bannier, Elise, Kerbrat, Anne, Cohen-Adad, Julien, and Barillot, Christian

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Physics - Medical Physics
Abstract

In Multiple Sclerosis (MS), there is a large discrepancy between the clinical observations and how the pathology is exhibited on brain images, this is known as the clinical-radiological paradox (CRP). One of the hypotheses is that the clinical deficit may be more related to the spinal cord damage than the number or location of lesions in the brain. Therefore, investigating how the spinal cord is damaged becomes an acute challenge to better understand and overcome the CRP. Diffusion MRI is known to provide quantitative figures of neuronal degeneration and axonal loss, in the brain as well as in the spinal cord. In this paper, we propose to investigate how diffusion MRI metrics vary in the different cervical regions with the progression of the disease. We first study the reproducibility of diffusion MRI on healthy volunteers with a test-retest procedure using both standard diffusion tensor imaging (DTI) and multi-compartment Ball-and-Stick models. Then, based on the test re-test quantitative calibration, we provide quantitative figures of pathology evolution between M0 and M12 in the cervical spine on a set of 31 MS patients, exhibiting how the pathology damage spans in the cervical spinal cord., Comment: Submitted to MICCAI 2018 (Weak Accept and 2 Weak reject)

Published
2021
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4. Consensus-based guidance for conducting and reporting multi-analyst studies

Author

Aczel, Balazs, Szaszi, Barnabas, Nilsonne, Gustav, van den Akker, Olmo R, Albers, Casper J, van Assen, Marcel ALM, Bastiaansen, Jojanneke A, Benjamin, Daniel, Boehm, Udo, Botvinik-Nezer, Rotem, Bringmann, Laura F, Busch, Niko A, Caruyer, Emmanuel, Cataldo, Andrea M, Cowan, Nelson, Delios, Andrew, van Dongen, Noah NN, Donkin, Chris, van Doorn, Johnny B, Dreber, Anna, Dutilh, Gilles, Egan, Gary F, Gernsbacher, Morton Ann, Hoekstra, Rink, Hoffmann, Sabine, Holzmeister, Felix, Huber, Juergen, Johannesson, Magnus, Jonas, Kai J, Kindel, Alexander T, Kirchler, Michael, Kunkels, Yoram K, Lindsay, D Stephen, Mangin, Jean-Francois, Matzke, Dora, Munafò, Marcus R, Newell, Ben R, Nosek, Brian A, Poldrack, Russell A, van Ravenzwaaij, Don, Rieskamp, Jörg, Salganik, Matthew J, Sarafoglou, Alexandra, Schonberg, Tom, Schweinsberg, Martin, Shanks, David, Silberzahn, Raphael, Simons, Daniel J, Spellman, Barbara A, St-Jean, Samuel, Starns, Jeffrey J, Uhlmann, Eric Luis, Wicherts, Jelte, and Wagenmakers, Eric-Jan

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Health Sciences, Consensus, Data Analysis, Datasets as Topic, Research, multi-analyst, metascience, statistical practice, science forum, expert consensus, analytical variability, None, medicine, neuroscience, none, Biochemistry and Cell Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Any large dataset can be analyzed in a number of ways, and it is possible that the use of different analysis strategies will lead to different results and conclusions. One way to assess whether the results obtained depend on the analysis strategy chosen is to employ multiple analysts and leave each of them free to follow their own approach. Here, we present consensus-based guidance for conducting and reporting such multi-analyst studies, and we discuss how broader adoption of the multi-analyst approach has the potential to strengthen the robustness of results and conclusions obtained from analyses of datasets in basic and applied research.

Published
2021

5. Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

Author

Girard, Gabriel, Rafael-Patiño, Jonathan, Truffet, Raphaël, Aydogan, Dogu Baran, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Bosticardo, Sara, Gabusi, Ilaria, Ocampo-Pineda, Mario, Battocchio, Matteo, Piskorova, Zuzana, Bontempi, Pietro, Schiavi, Simona, Daducci, Alessandro, Stafiej, Aleksandra, Ciupek, Dominika, Bogusz, Fabian, Pieciak, Tomasz, Frigo, Matteo, Sedlar, Sara, Deslauriers-Gauthier, Samuel, Kojčić, Ivana, Zucchelli, Mauro, Laghrissi, Hiba, Ji, Yang, Deriche, Rachid, Schilling, Kurt G, Landman, Bennett A., Cacciola, Alberto, Basile, Gianpaolo Antonio, Bertino, Salvatore, Newlin, Nancy, Kanakaraj, Praitayini, Rheault, Francois, Filipiak, Patryk, Shepherd, Timothy M., Lin, Ying-Chia, Placantonakis, Dimitris G., Boada, Fernando E., Baete, Steven H., Hernández-Gutiérrez, Erick, Ramírez-Manzanares, Alonso, Coronado-Leija, Ricardo, Stack-Sánchez, Pablo, Concha, Luis, Descoteaux, Maxime, Mansour L．, Sina, Seguin, Caio, Zalesky, Andrew, Marshall, Kenji, Canales-Rodríguez, Erick J., Wu, Ye, Ahmad, Sahar, Yap, Pew-Thian, Théberge, Antoine, Gagnon, Florence, Massi, Frédéric, Fischi-Gomez, Elda, Gardier, Rémy, Haro, Juan Luis Villarreal, Pizzolato, Marco, Caruyer, Emmanuel, and Thiran, Jean-Philippe

Published
2023
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6. The Microstructural Features of the Diffusion-Simulated Connectivity (DiSCo) Dataset

Author

Rafael-Patino, Jonathan, Girard, Gabriel, Truffet, Raphaël, Pizzolato, Marco, Thiran, Jean-Philippe, Caruyer, Emmanuel, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cetin-Karayumak, Suheyla, editor, Christiaens, Daan, editor, Figini, Matteo, editor, Guevara, Pamela, editor, Gyori, Noemi, editor, Nath, Vishwesh, editor, and Pieciak, Tomasz, editor

Published
2021
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7. An Evolutionary Framework for Microstructure-Sensitive Generalized Diffusion Gradient Waveforms

Author

Truffet, Raphaël, Rafael-Patino, Jonathan, Girard, Gabriel, Pizzolato, Marco, Barillot, Christian, Thiran, Jean-Philippe, Caruyer, Emmanuel, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Martel, Anne L., editor, Abolmaesumi, Purang, editor, Stoyanov, Danail, editor, Mateus, Diana, editor, Zuluaga, Maria A., editor, Zhou, S. Kevin, editor, Racoceanu, Daniel, editor, and Joskowicz, Leo, editor

Published
2020
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8. Characterizing Peritumoral Tissue Using DTI-Based Free Water Elimination

Author

Ould Ismail, Abdol Aziz, Parker, Drew, Hernandez-Fernandez, Moises, Brem, Steven, Alexander, Simon, Pasternak, Ofer, Caruyer, Emmanuel, Verma, Ragini, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Crimi, Alessandro, editor, Bakas, Spyridon, editor, Kuijf, Hugo, editor, Keyvan, Farahani, editor, Reyes, Mauricio, editor, and van Walsum, Theo, editor

Published
2019
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9. Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization

Author

Canales-Rodríguez, Erick J., Daducci, Alessandro, Sotiropoulos, Stamatios N., Caruyer, Emmanuel, Aja-Fernández, Santiago, Radua, Joaquim, Mendizabal, Jesús María Yurramendi, Iturria-Medina, Yasser, Melie-García, Lester, Alemán-Gómez, Yasser, Thiran, Jean-Philippe, Sarró, Salvador, Pomarol-Clotet, Edith, and Salvador, Raymond

Subjects
Physics - Medical Physics
Abstract

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on the methodology used to combine multichannel signals. Indeed, the two prevailing methods for multichannel signal combination lead to Rician and noncentral Chi noise distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in brain data.

Published
2014
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13. Similarity Metrics for Diffusion Multi-Compartment Model Images Registration

Author

Commowick, Olivier, Hédouin, Renaud, Caruyer, Emmanuel, Barillot, Christian, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Descoteaux, Maxime, editor, Maier-Hein, Lena, editor, Franz, Alfred, editor, Jannin, Pierre, editor, Collins, D. Louis, editor, and Duchesne, Simon, editor

Published
2017
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15. Tractography passes the test:Results from the diffusion-simulated connectivity (disco) challenge

Author

Girard, Gabriel, Rafael-Patiño, Jonathan, Truffet, Raphaël, Aydogan, Dogu Baran, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Bosticardo, Sara, Gabusi, Ilaria, Ocampo-Pineda, Mario, Battocchio, Matteo, Piskorova, Zuzana, Bontempi, Pietro, Schiavi, Simona, Daducci, Alessandro, Stafiej, Aleksandra, Ciupek, Dominika, Bogusz, Fabian, Pieciak, Tomasz, Frigo, Matteo, Sedlar, Sara, Deslauriers-Gauthier, Samuel, Kojčić, Ivana, Zucchelli, Mauro, Laghrissi, Hiba, Ji, Yang, Deriche, Rachid, Schilling, Kurt G., Landman, Bennett A., Cacciola, Alberto, Basile, Gianpaolo Antonio, Bertino, Salvatore, Newlin, Nancy, Kanakaraj, Praitayini, Rheault, Francois, Filipiak, Patryk, Shepherd, Timothy M., Lin, Ying Chia, Placantonakis, Dimitris G., Boada, Fernando E., Baete, Steven H., Hernández-Gutiérrez, Erick, Ramírez-Manzanares, Alonso, Coronado-Leija, Ricardo, Stack-Sánchez, Pablo, Concha, Luis, Descoteaux, Maxime, Mansour L．, Sina, Seguin, Caio, Zalesky, Andrew, Marshall, Kenji, Canales-Rodríguez, Erick J., Wu, Ye, Ahmad, Sahar, Yap, Pew Thian, Théberge, Antoine, Gagnon, Florence, Massi, Frédéric, Fischi-Gomez, Elda, Gardier, Rémy, Haro, Juan Luis Villarreal, Pizzolato, Marco, Caruyer, Emmanuel, Thiran, Jean Philippe, Girard, Gabriel, Rafael-Patiño, Jonathan, Truffet, Raphaël, Aydogan, Dogu Baran, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Bosticardo, Sara, Gabusi, Ilaria, Ocampo-Pineda, Mario, Battocchio, Matteo, Piskorova, Zuzana, Bontempi, Pietro, Schiavi, Simona, Daducci, Alessandro, Stafiej, Aleksandra, Ciupek, Dominika, Bogusz, Fabian, Pieciak, Tomasz, Frigo, Matteo, Sedlar, Sara, Deslauriers-Gauthier, Samuel, Kojčić, Ivana, Zucchelli, Mauro, Laghrissi, Hiba, Ji, Yang, Deriche, Rachid, Schilling, Kurt G., Landman, Bennett A., Cacciola, Alberto, Basile, Gianpaolo Antonio, Bertino, Salvatore, Newlin, Nancy, Kanakaraj, Praitayini, Rheault, Francois, Filipiak, Patryk, Shepherd, Timothy M., Lin, Ying Chia, Placantonakis, Dimitris G., Boada, Fernando E., Baete, Steven H., Hernández-Gutiérrez, Erick, Ramírez-Manzanares, Alonso, Coronado-Leija, Ricardo, Stack-Sánchez, Pablo, Concha, Luis, Descoteaux, Maxime, Mansour L．, Sina, Seguin, Caio, Zalesky, Andrew, Marshall, Kenji, Canales-Rodríguez, Erick J., Wu, Ye, Ahmad, Sahar, Yap, Pew Thian, Théberge, Antoine, Gagnon, Florence, Massi, Frédéric, Fischi-Gomez, Elda, Gardier, Rémy, Haro, Juan Luis Villarreal, Pizzolato, Marco, Caruyer, Emmanuel, and Thiran, Jean Philippe

Abstract

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

Published
2023

16. Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord

Author

Snoussi, Haykel, Cohen-Adad, Julien, Combès, Benoît, Bannier, Élise, Tounekti, Slimane, Kerbrat, Anne, Barillot, Christian, Caruyer, Emmanuel, Snoussi, Haykel, Cohen-Adad, Julien, Combès, Benoît, Bannier, Élise, Tounekti, Slimane, Kerbrat, Anne, Barillot, Christian, and Caruyer, Emmanuel

Abstract

Introduction Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is widely used for MS diagnosis and clinical follow-up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball-and-Stick models. Methods We analyzed spinal cord data acquired from multiple hospitals and extracted average diffusion MRI metrics per vertebral level using a collection of image processing methods and an atlas-based approach. We then performed a statistical analysis to evaluate the feasibility of these metrics for detecting lesions, exploring the usefulness of combining different metrics to improve accuracy. Results Our study demonstrates the sensitivity of each metric to underlying microstructure changes in MS patients. We show that selecting a specific subset of metrics, which provide complementary information, significantly improves the prediction score of lesion presence in the cervical spinal cord. Furthermore, the Ball-and-Stick model has the potential to provide novel information about the microstructure of damaged tissue. Conclusion Our results suggest that diffusion measures, particularly combined measures, are sensitive in discriminating abnormal from healthy cervical vertebral levels in patients. This information could aid in improving MS diagnosis and clinical follow-up. Our study highlights the potential of the Ball-and-Stick model in providing additional insights into the microstructure of the damaged tissue.

Published
2023

17. Étude de l’effet du bruit sur l'estimation de l'anisotropie microscopique en IRM de diffusion

Author

Bocquillon, Constance, Lapert, Marc, Bannier, Elise, Corouge, Isabelle, Caruyer, Emmanuel, Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Siemens Healthcare [France], Siemens AG [Munich], and CHU Pontchaillou [Rennes]

Subjects
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Abstract

International audience

Published
2023

18. Reproductibilité d'une tâche motrice en NIRS et comparaison à l'IRMf BOLD sur des sujets adultes sains

Author

Jégou, Nolwenn, Bannier, Elise, Erhart, Nora, Garcia, Hector H, Caruyer, Emmanuel, Corouge, Isabelle, Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département de Radiologie [CHU de Rennes], Université de Rennes (UR), Instituto de Física Arroyo Seco [Tandil] (IFAS), Section for Biomedical Image Analysis (SBIA), Perelman School of Medicine, and University of Pennsylvania-University of Pennsylvania

Subjects
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Abstract

International audience; Objectifs : La NIRS, comme l'IRMf BOLD, fournit une mesure indirecte de l'activité cérébrale au travers des variations hémodynamiques. Cette technique d'imagerie portable est plus accessible que l'IRMf mais serait moins reproductible, en particulier au niveau individuel [1]. Cette étude évalue la reproductibilité NIRS d'une tâche motrice en test-retest en comparaison avec l'IRMf.

Published
2023

19. Author Correction: The challenge of mapping the human connectome based on diffusion tractography

Author

Maier-Hein, Klaus H., Neher, Peter F., Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E., Glass, John O., Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, He, Renjie, Li, Qiang, Westin, Carl-Fredrik, Deslauriers-Gauthier, Samuel, González, J. Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M. W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H. Ertan, Odry, Benjamin L., Mailhe, Boris, Nadar, Mariappan S., Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E., Galvis, Justin, Thompson, Paul M., De Santiago Requejo, Francisco, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell’Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B., Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, and Descoteaux, Maxime

Published
2019
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21. Parametric Dictionary Learning for Modeling EAP and ODF in Diffusion MRI

Author

Merlet, Sylvain, Caruyer, Emmanuel, Deriche, Rachid, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ayache, Nicholas, editor, Delingette, Hervé, editor, Golland, Polina, editor, and Mori, Kensaku, editor

Published
2012
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22. Impact of Radial and Angular Sampling on Multiple Shells Acquisition in Diffusion MRI

Author

Merlet, Sylvain, Caruyer, Emmanuel, Deriche, Rachid, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Fichtinger, Gabor, editor, Martel, Anne, editor, and Peters, Terry, editor

Published
2011
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23. Numerical methods for white matter microstructure and brain structural connectivity in diffusion MRI

Author

Caruyer, Emmanuel, Caruyer, Emmanuel, Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Université de Rennes 1, and Patrick Bouthemy

Subjects
[SCCO.COMP] Cognitive science/Computer science, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, magnetic resonance imaging, [SCCO.COMP]Cognitive science/Computer science, Neuroimaging, Brain microstructure, Diffusion mri, Imagerie médicale
Published
2022

24. Imagerie par résonance magnétique de diffusion

Author

Caruyer, Emmanuel, Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), and Caruyer, Emmanuel

Subjects
[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
Abstract

International audience; L’imagerie par résonance magnétique (IRM) est une technique non invasive, ne nécessitant pas d’injection de produit de contraste, qui s’est imposée comme outil d’aide au diagnostic et de suivi d’un grand nombre de pathologies. Depuis sa découverte au milieu des années 1970, l’IRM s’est déclinée en différentes modalités, permettant d’observer et de mesurer des caractéristiques aussi diverses que l’anatomie des organes, l’élasticité des tissus, le fonctionnement métabolique des neurones ou encore la circulation du sang à l’intérieur des vaisseaux capillaires. Parmi ces modalités, l’IRM dite « de diffusion » permet de mesurer la diffusion des molécules d’eau qui décrivent des mouvements spontanés et aléatoires, en raison de l’agitation thermique. Comme ces mouvements sont limités par la présence des tissus, ils nous renseignent sur l’organisation et la structure de ceux-ci, à une échelle beaucoup plus fine que la résolution standard des images. Dans cet article, nous présentons de façon simplifiée les principes de la résonance magnétique nucléaire et de l’imagerie par résonance magnétique (IRM), puis le lien entre l’IRM de diffusion et la microstructure des tissus et, enfin, quelques ­applications en neuroimagerie.

Published
2022

26. The challenge of mapping the human connectome based on diffusion tractography

Author

Maier-Hein, Klaus H., Neher, Peter F., Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E., Glass, John O., Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, He, Renjie, Li, Qiang, Westin, Carl-Fredrik, Deslauriers-Gauthier, Samuel, González, J. Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M. W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H. Ertan, Odry, Benjamin L., Mailhe, Boris, Nadar, Mariappan S., Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E., Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell’Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B., Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, and Descoteaux, Maxime

Published
2017
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28. Le corps en images: Les nouvelles imageries pour la santé

Author

Blanc-Féraud, Laure, Caruyer, Emmanuel, Jutten, Christian, Liebgott, Herve, Morphologie et Images (MORPHEME), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut de Biologie Valrose (IBV), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Signal, Images et Systèmes (Laboratoire I3S - SIS), Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), GIPSA - Vision and Brain Signal Processing (GIPSA-VIBS), GIPSA Pôle Sciences des Données (GIPSA-PSD), Grenoble Images Parole Signal Automatique (GIPSA-lab), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Grenoble Alpes (UGA), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
Abstract

International audience; Au cours des dernières décennies, les progrès technologiques ont débouché sur le développement de nouveaux capteurs et des moyens de calculs très performants permettant l’acquisition et le traitement très rapide, voire en temps réel, de très grandes quantités de signaux et d’images. Ces avancées ont impacté de nombreux domaines, aboutissant dans le secteur de la santé à des techniques révolutionnaires pour visualiser le corps.Ces nouvelles imageries pour la santé incluent des méthodes de visualisation des organes jusqu’à l’échelle cellulaire ou moléculaire, des méthodes d’évaluation permettant de vérifier le bon fonctionnement des organes, et des méthodes de suivi interventionnel permettant de guider les gestes du praticien hospitalier ou du chirurgien.L’apport des sciences du numérique et de l’intelligence artificielle est essentiel pour ces nouvelles technologies, et permet au corps médical d’analyser rapidement de très grandes quantités d’images, de les traiter conjointement lorsqu’elles proviennent de différents dispositifs et d’exploiter les données des praticiens du monde entier. Mais l’utilisation de ces nouvelles technologies pose également des problèmes sociétaux, notamment de formation des soignants et d’acceptation, tant par le patient que par le praticien. Enfin, le partage de données médicales soulève des questions d’éthique et de préservation de la vie privée.Abondamment illustré, en 17 articles indépendants, Le corps en images aborde toutes ces questions et présente les progrès récents et les perspectives de l’imagerie médicale, un domaine qui nous concerne tous.

Published
2022

29. SANDI-AMICO: an open-source toolbox for fast Soma And Neurite Density Imaging (SANDI) with AMICO

Author

Schiavi, Simona, Ocampo-Pineda, Mario, Truffet, Raphaël, Caruyer, Emmanuel, Daducci, Alessandro, Palombo, Marco, Department of Computer Science [Verona] (UNIVR | DI), Università degli studi di Verona = University of Verona (UNIVR), Università degli studi di Genova = University of Genoa (UniGe), Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Neuroimagerie: méthodes et applications (EMPENN), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), University College of London [London] (UCL), Cardiff University's Brain Research Imaging Centre [Cardiff] (CUBRIC), School of Psychology [Cardiff University], Cardiff University-Cardiff University, Cardiff University, and Caruyer, Emmanuel

Subjects
[SCCO.COMP] Cognitive science/Computer science, [SCCO.COMP]Cognitive science/Computer science
Abstract

International audience; The soma and neurite density imaging (SANDI) model has been recently introduced to estimate diffusion MRI indices of apparent neurite and soma density noninvasively in the brain. Here, we introduce SANDIAMICO a fast (10 seconds for whole brain images) and robust implementation for estimating SANDI parameters using the Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework. Using numerical simulations and in vivo human data, we show excellent performances of SANDIAMICO in terms of accuracy, precision, robustness to noise and intra-subject reproducibility.

Published
2021

32. Reproducibility of motor task-based fNIRS and comparison with functional MRI in healthy adults

Author

Jégou, Nolwenn, Bannier, Elise, Erhart, Nora, Garcia, Hector H, Caruyer, Emmanuel, Corouge, Isabelle, Jégou, Nolwenn, Neuroimagerie: méthodes et applications (EMPENN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAL, IMAGE ET LANGAGE (IRISA-D6), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Département de Radiologie [CHU de Rennes], Université de Rennes (UR), Centro de Investigaciones en Física e Ingeniería del Centro [Buenos Aires], and Instituto de Física Arroyo Seco [Tandil] (IFAS)

Subjects
[INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Abstract

International audience; We studied the ability and reproducibility of fNIRS to map the cortical motor areas. Simultaneously acquired fMRI was used as a reference and functional maps of both modalities were obtained from GLM analysis. NIRS results show satisfactory reproducibility but partial agreement with fMRI.

Published
2022

33. Consensus-based guidance for conducting and reporting multi-analyst studies

Author

Aczel, Balazs, primary, Szaszi, Barnabas, primary, Nilsonne, Gustav, additional, van den Akker, Olmo R, additional, Albers, Casper J, additional, van Assen, Marcel ALM, additional, Bastiaansen, Jojanneke A, additional, Benjamin, Daniel, additional, Boehm, Udo, additional, Botvinik-Nezer, Rotem, additional, Bringmann, Laura F, additional, Busch, Niko A, additional, Caruyer, Emmanuel, additional, Cataldo, Andrea M, additional, Cowan, Nelson, additional, Delios, Andrew, additional, van Dongen, Noah NN, additional, Donkin, Chris, additional, van Doorn, Johnny B, additional, Dreber, Anna, additional, Dutilh, Gilles, additional, Egan, Gary F, additional, Gernsbacher, Morton Ann, additional, Hoekstra, Rink, additional, Hoffmann, Sabine, additional, Holzmeister, Felix, additional, Huber, Juergen, additional, Johannesson, Magnus, additional, Jonas, Kai J, additional, Kindel, Alexander T, additional, Kirchler, Michael, additional, Kunkels, Yoram K, additional, Lindsay, D Stephen, additional, Mangin, Jean-Francois, additional, Matzke, Dora, additional, Munafò, Marcus R, additional, Newell, Ben R, additional, Nosek, Brian A, additional, Poldrack, Russell A, additional, van Ravenzwaaij, Don, additional, Rieskamp, Jörg, additional, Salganik, Matthew J, additional, Sarafoglou, Alexandra, additional, Schonberg, Tom, additional, Schweinsberg, Martin, additional, Shanks, David, additional, Silberzahn, Raphael, additional, Simons, Daniel J, additional, Spellman, Barbara A, additional, St-Jean, Samuel, additional, Starns, Jeffrey J, additional, Uhlmann, Eric Luis, additional, Wicherts, Jelte, additional, and Wagenmakers, Eric-Jan, additional

Published
2021
Full Text
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34. Author response: Consensus-based guidance for conducting and reporting multi-analyst studies

Author

Aczel, Balazs, primary, Szaszi, Barnabas, primary, Nilsonne, Gustav, additional, van den Akker, Olmo R, additional, Albers, Casper J, additional, van Assen, Marcel ALM, additional, Bastiaansen, Jojanneke A, additional, Benjamin, Daniel, additional, Boehm, Udo, additional, Botvinik-Nezer, Rotem, additional, Bringmann, Laura F, additional, Busch, Niko A, additional, Caruyer, Emmanuel, additional, Cataldo, Andrea M, additional, Cowan, Nelson, additional, Delios, Andrew, additional, van Dongen, Noah NN, additional, Donkin, Chris, additional, van Doorn, Johnny B, additional, Dreber, Anna, additional, Dutilh, Gilles, additional, Egan, Gary F, additional, Gernsbacher, Morton Ann, additional, Hoekstra, Rink, additional, Hoffmann, Sabine, additional, Holzmeister, Felix, additional, Huber, Juergen, additional, Johannesson, Magnus, additional, Jonas, Kai J, additional, Kindel, Alexander T, additional, Kirchler, Michael, additional, Kunkels, Yoram K, additional, Lindsay, D Stephen, additional, Mangin, Jean-Francois, additional, Matzke, Dora, additional, Munafò, Marcus R, additional, Newell, Ben R, additional, Nosek, Brian A, additional, Poldrack, Russell A, additional, van Ravenzwaaij, Don, additional, Rieskamp, Jörg, additional, Salganik, Matthew J, additional, Sarafoglou, Alexandra, additional, Schonberg, Tom, additional, Schweinsberg, Martin, additional, Shanks, David, additional, Silberzahn, Raphael, additional, Simons, Daniel J, additional, Spellman, Barbara A, additional, St-Jean, Samuel, additional, Starns, Jeffrey J, additional, Uhlmann, Eric Luis, additional, Wicherts, Jelte, additional, and Wagenmakers, Eric-Jan, additional

Published
2021
Full Text
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36. Guidance for Multi-Analyst Studies

Author

St-Jean, Samuel, Dreber , Anna, Matzke , Dora, Schonberg , Tom, Spellman , Bobbie, Wagenmakers , Eric-Jan, Starns , Jeffrey, Benjamin , Daniel, Caruyer, Emmanuel, Newell , Ben, van Doorn , Johnny, Uhlmann , Eric, Van den Akker , Olmo, Mangin, Jan-Francois, Busch , Niko, Kindel, Alexander, Delios , Andrew, Munafo , Marcus, Kunkels , Yoram, Jonas , Kai, Schweinsberg , Martin, Wicherts , Jelte, Hoffmann , Sabine, Simons , Daniel, Sarafoglou , Alexandra, Gernsbacher , Morton Ann, van Assen , Marcel, Shanks , David, Hoekstra , Rink, Albers , Casper, Lindsay , D., Szaszi , Barnabas, van Dongen , Noah, Bastiaansen , Jojanneke, Kirchler , Michael, Dutilh , Gilles, Cowan , Nelson, Holzmeister, Felix, Cataldo , Andrea, Boehm , Udo, Johannesson , Magnus, Botvinik-Nezer , Rotem, Rieskamp , Jörg, Nilsonne , Gustav, Salganik , Matthew, Poldrack , Russell, Egan, Gary, van Ravenzwaaij , Don, Silberzahn , Raphael, Bringmann , Laura, Nosek , Brian, Donkin , Chris, and Aczel , Balazs

Subjects
bepress|Social and Behavioral Sciences|Other Social and Behavioral Sciences, MetaArXiv|Social and Behavioral Sciences, MetaArXiv|Social and Behavioral Sciences|Other Social and Behavioral Sciences, bepress|Social and Behavioral Sciences, ComputingMilieux_MISCELLANEOUS
Abstract

We present consensus-based guidance for conducting and documenting multi-analyst studies. We discuss why broader adoption of the multi-analyst approach will strengthen the robustness of results and conclusions in empirical sciences.

Published
2021

37. The Diffusion-Simulated Connectivity (DiSCo) Dataset

Author

Rafael-Patino, Jonathan, Girard, Gabriel, Truffet, Raphal, Pizzolato, Marco, Caruyer, Emmanuel, Thiran, Jean-Philippe, Rafael-Patino, Jonathan, Girard, Gabriel, Truffet, Raphal, Pizzolato, Marco, Caruyer, Emmanuel, and Thiran, Jean-Philippe

Abstract

The methodological development in the mapping of the brain structural connectome from diffusion-weighted magnetic resonance imaging (DW-MRI) has raised many hopes in the neuroscientific community. Indeed, the knowledge of the connections between different brain regions is fundamental to study brain anatomy and function. The reliability of the structural connectome is therefore of paramount importance. In the search for accuracy, researchers have given particular attention to linking white matter tractography methods – used for estimating the connectome – with information about the microstructure of the nervous tissue. The creation and validation of methods in this context were hampered by a lack of practical numerical phantoms. To achieve this, we created a numerical phantom that mimics complex anatomical fibre pathway trajectories while also accounting for microstructural features such as axonal diameter distribution, myelin presence, and variable packing densities. The substrate has a micrometric resolution and an unprecedented size of 1 cubic millimetre to mimic an image acquisition matrix of 40x40x40 voxels. DW-MRI images were obtained from Monte Carlo simulations of spin dynamics to enable the validation of quantitative tractography. The phantom is composed of 12,196 synthetic tubular fibres with diameters ranging from 1.4 µm to 4.2 µm, interconnecting sixteen regions of interest. The simulated images capture the microscopic properties of the tissue (e.g. fibre diameter, water diffusing within and around fibres, free water compartment), while also having desirable macroscopic properties resembling the anatomy, such as the smoothness of the fibre trajectories. While previous phantoms were used to validate either tractography or microstructure, this phantom can enable a better assessment of the connectome estimation’s reliability on the one side, and its adherence to the actual microstructure of the nervous tissue on the other.

Published
2021

38. An Evolutionary Framework for Microstructure-Sensitive Generalized Diffusion Gradient Waveforms

Author

Martel, Anne L., Abolmaesumi, Purang, Stoyanov, Danail, Mateus, Diana, Zuluaga, Maria A., Zhou, S. Kevin, Racoceanu, Daniel, Joskowicz, Leo, Truffet, Raphaël, Rafael-Patino, Jonathan, Girard, Gabriel, Pizzolato, Marco, Barillot, Christian, Thiran, Jean Philippe, Caruyer, Emmanuel, Martel, Anne L., Abolmaesumi, Purang, Stoyanov, Danail, Mateus, Diana, Zuluaga, Maria A., Zhou, S. Kevin, Racoceanu, Daniel, Joskowicz, Leo, Truffet, Raphaël, Rafael-Patino, Jonathan, Girard, Gabriel, Pizzolato, Marco, Barillot, Christian, Thiran, Jean Philippe, and Caruyer, Emmanuel

Abstract

In diffusion-weighted MRI, general gradient waveforms became of interest for their sensitivity to microstructure features of the brain white matter. However, the design of such waveforms remains an open problem. In this work, we propose a framework for generalized gradient waveform design with optimized sensitivity to selected microstructure features. In particular, we present a rotation-invariant method based on a genetic algorithm to maximize the sensitivity of the signal to the intra-axonal volume fraction. The sensitivity is evaluated by computing a score based on the Fisher information matrix from Monte-Carlo simulations, which offer greater flexibility and realism than conventional analytical models. As proof of concept, we show that the optimized waveforms have higher scores than the conventional pulsed-field gradients experiments. Finally, the proposed framework can be generalized to optimize the waveforms for to any microstructure feature of interest.

Published
2020

42. Optimal selection of diffusion-weighting gradient waveforms using compressed sensing and dictionary learning

Author

Truffet, Raphaël, Caruyer, Emmanuel, Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Truffet, Raphaël

Subjects
[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2018

43. Freewater EstimatoR using iNtErpolated iniTialization (FERNET): Toward Accurate Estimation of Free Water in Peritumoral Region Using Single-Shell Diffusion MRI Data

Author

Ould Ismail, Abdol Aziz, primary, Parker, Drew, additional, Hernandez-Fernandez, Moises, additional, Wolf, Ronald, additional, Brem, Steven, additional, Alexander, Simon, additional, Hodges, Wes, additional, Pasternak, Ofer, additional, Caruyer, Emmanuel, additional, and Verma, Ragini, additional

Published
2019
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45. Comparison of inhomogeneity distortion correction methods in diffusion MRI of the spinal cord

Author

Snoussi , Haykel, Caruyer , Emmanuel, Commowick , Olivier, Bannier , Elise, Barillot , Christian, Vision, Action et Gestion d'informations en Santé ( VisAGeS ), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE ( IRISA_D5 ), Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées - Rennes ( INSA Rennes ), Institut National des Sciences Appliquées ( INSA ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées ( INSA ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Université de Rennes 1 ( UR1 ), Institut National des Sciences Appliquées ( INSA ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées ( INSA ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ) -Institut de Recherche en Informatique et Systèmes Aléatoires ( IRISA ), Institut National des Sciences Appliquées ( INSA ) -Université de Rennes ( UNIV-RENNES ) -Institut National des Sciences Appliquées ( INSA ) -Université de Bretagne Sud ( UBS ) -École normale supérieure - Rennes ( ENS Rennes ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -IMT Atlantique Bretagne-Pays de la Loire ( IMT Atlantique ), Département de Radiologie [CHU de Rennes], and Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES )

Subjects
[ SDV.IB ] Life Sciences [q-bio]/Bioengineering
Abstract

Scientific Session; International audience; Purpose / IntroductionDiffusion MRI (dMRI) is a modality that describes the geometry of neural architecture. Diffusion images suffer from various artifacts originating from subject and physiological motion, eddy currents and B0-field inhomogeneity. These can severely affect image quality particularly in the spine region. However, strategies exist to correct these distortions, including co-registration, point spread function, phase field map and reversed gradient polarity method (RGPM). In this work, we focus on the comparative evaluation of correction methods using RGPM which provides best results [1]. More precisely, we compare Voss [1,2] plus two other recent methods: FSL’s Topup [3] and SPM’s HySCO [4].

Published
2017

46. The challenge of mapping the human connectome based on diffusion tractography

Author

Maier-Hein, Klaus H, Neher, Peter F, Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E, Glass, John O, Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, Renjie, H, Li, Qiang, Westin, Carl Fredrik, Deslauriers-Gauthier, Samuel, González, J Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M.W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H Ertan, Odry, Benjamin L, Mailhe, Boris, Nadar, Mariappan S, Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E, Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell'Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B, Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, Descoteaux, Maxime, Maier-Hein, Klaus H, Neher, Peter F, Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E, Glass, John O, Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, Renjie, H, Li, Qiang, Westin, Carl Fredrik, Deslauriers-Gauthier, Samuel, González, J Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M.W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H Ertan, Odry, Benjamin L, Mailhe, Boris, Nadar, Mariappan S, Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E, Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell'Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B, Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, and Descoteaux, Maxime

Published
2017

47. The challenge of mapping the human connectome based on diffusion tractography

Author

Beeldverwerking ISI, Brain, UMC Utrecht, Highfield Research Group, Maier-Hein, Klaus H, Neher, Peter F, Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E, Glass, John O, Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, Renjie, H, Li, Qiang, Westin, Carl Fredrik, Deslauriers-Gauthier, Samuel, González, J Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M.W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H Ertan, Odry, Benjamin L, Mailhe, Boris, Nadar, Mariappan S, Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E, Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell'Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B, Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, Descoteaux, Maxime, Beeldverwerking ISI, Brain, UMC Utrecht, Highfield Research Group, Maier-Hein, Klaus H, Neher, Peter F, Houde, Jean-Christophe, Côté, Marc-Alexandre, Garyfallidis, Eleftherios, Zhong, Jidan, Chamberland, Maxime, Yeh, Fang-Cheng, Lin, Ying-Chia, Ji, Qing, Reddick, Wilburn E, Glass, John O, Chen, David Qixiang, Feng, Yuanjing, Gao, Chengfeng, Wu, Ye, Ma, Jieyan, Renjie, H, Li, Qiang, Westin, Carl Fredrik, Deslauriers-Gauthier, Samuel, González, J Omar Ocegueda, Paquette, Michael, St-Jean, Samuel, Girard, Gabriel, Rheault, François, Sidhu, Jasmeen, Tax, Chantal M.W., Guo, Fenghua, Mesri, Hamed Y., Dávid, Szabolcs, Froeling, Martijn, Heemskerk, Anneriet M., Leemans, Alexander, Boré, Arnaud, Pinsard, Basile, Bedetti, Christophe, Desrosiers, Matthieu, Brambati, Simona, Doyon, Julien, Sarica, Alessia, Vasta, Roberta, Cerasa, Antonio, Quattrone, Aldo, Yeatman, Jason, Khan, Ali R., Hodges, Wes, Alexander, Simon, Romascano, David, Barakovic, Muhamed, Auría, Anna, Esteban, Oscar, Lemkaddem, Alia, Thiran, Jean-Philippe, Cetingul, H Ertan, Odry, Benjamin L, Mailhe, Boris, Nadar, Mariappan S, Pizzagalli, Fabrizio, Prasad, Gautam, Villalon-Reina, Julio E, Galvis, Justin, Thompson, Paul M., Requejo, Francisco De Santiago, Laguna, Pedro Luque, Lacerda, Luis Miguel, Barrett, Rachel, Dell'Acqua, Flavio, Catani, Marco, Petit, Laurent, Caruyer, Emmanuel, Daducci, Alessandro, Dyrby, Tim B, Holland-Letz, Tim, Hilgetag, Claus C., Stieltjes, Bram, and Descoteaux, Maxime

Published
2017

48. IRM de diffusion du Q-space : Acquisition et pré-traitements

Author

Caruyer, Emmanuel, Caruyer, Emmanuel, Computational Imaging of the Central Nervous System (ATHENA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Nice Sophia Antipolis, Rachid Deriche(Rachid.Deriche@inria.fr), and Equipe Associée CD-MRI

Subjects
détection de mouvement, régularisation de Laplace, q-ball imaging, échantillonnage dans l'espace de Fourier, acquisition sphérique, regularized reconstruction, reconstruction sous contrainte de régularité, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC], IRM de diffusion, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], filtre de Kalman, q-space sampling, diffusion MRI, Laplace regularization, acquisition sequence, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, motion detection, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], séquence d'acquisition, Kalman filtering, [PHYS.PHYS.PHYS-DATA-AN] Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an], [PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis, Statistics and Probability [physics.data-an], [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Abstract

The overall goal of this thesis is to develop novel methods for the acquisition and the processing of diffusion magnetic resonance images (MRI), to provide new insights into the structure and anatomy of the brain white matter in vivo. Diffusion MRI is a non-invasive technique that measures locally the diffusion of water molecules. The latter are hindered by tissue structure, and therefore the characterization of water molecules displacement gives information on the nature, orientation, microstructure of the underlying tissue. Because of the strong anisotropy observed in white matter fiber tracts, this tool is most popular for the analysis of brain connectivity. One of the modality of acquisition and reconstruction, called diffusion tensor imaging, is now an established tool in research and clinical applications, for the detection of neural diseases and for pre-operative planning. Being model-based, the diffusion tensor cannot describe complex intra-voxel configurations, with multiple populations of fibers crossing. Since then, for a finer description of water molecules displacement, model-free approaches have recently been proposed, aiming at overcome the limitations of the diffusion tensor. Most of these techniques are still extremely demanding in acquisition time, and involve challenging reconstruction problems. The first part of this thesis proceeds from a description of the tissue microstructure, and a physical explanation of the origin of acquired diffusion signal. We give a review of the reconstruction methods and corresponding acquisition techniques in diffusion MRI. Several reconstruction methods are presented, and are categorized into model-based and model-free techniques. The first contribution of this thesis is related to the parametric reconstruction of the diffusion signal in a continuous basis of functions. We develop on a previous proposed method called Spherical Polar Fourier basis, and propose a continuous basis with a significant reduction of the dimension for the same power of description. We also derive the expression of the Laplace regularization operator in this basis, for a better robustness to noise. The second contribution is also related to the reconstruction of the diffusion signal, and the orientation distribution function, with a special focus on clinical setting. We propose a real-time reconstruction algorithm based on the Kalman filter to reconstruct the ODF in constant solid angle. We develop on top of the Kalman filter a motion detection algorithm, based on a monitoring and statistical analysis of the Kalman filter residuals. We are able to give a precise and sensitive motion detection, at no additional cost on the on-line acquisition system, as compared to systems based on camera and computer vision. The two last contributions are related to the acquisition methods in diffusion MRI, in particular for single and multiple $q$-shell experiments. We first describe a geometric approach to generate angular uniform schemes, that offer optimal angular coverage per shell and as a whole. Then we investigate on the link between the choice of a parametric basis of functions, and the design of sampling protocols. We give explicit methods to generate sampling schemes with minimal condition number, for the reconstruction in spherical harmonics (in Q-ball imaging) and the reconstruction in the modified spherical polar Fourier basis, proposed in this thesis. The conclusion of this approach is that the sampling method should be driven by the physical constraints of the scanner, and at the same time by the choice of a specific basis to represent the diffusion signal, and with an overall uniform coverage of the space of sampling directions, for a good rotational invariance. The new sampling schemes generated with this technique are available for download from my web page., Le but général de cette thèse est de proposer de nouvelles méthodes d'acquisition et de traitement du signal en imagerie par résonance magnétique (IRM) de diffusion, dans le but d'ouvrir de nouvelles perspectives dans la reconstruction de la structure de la matière blanche \emph{in vivo}. L'IRM de diffusion est une technique d'imagerie non invasive qui mesure localement, en chaque voxel, la diffusion des molécules d'eau. Le déplacement de ces dernières étant contraint par la présence de tissus, le fait de pouvoir caractériser la diffusion des molécules d'eau apporte des informations sur la nature, l'orientation, la microstructure des tissus biologiques sous-jacents. La forte anisotropie observée dans la matière blanche fait de l'IRM de diffusion un outil privilégié pour l'étude de la connectivité cérébrale. Une des premières techniques d'acquisition et de reconstruction, appelée IRM du tenseur de diffusion, est maintenant utilisée de manière routinière en clinique, pour le diagnostique de certaines maladies neurologiques, ou encore en planification préopératoire. L'IRM du tenseur de diffusion repose sur un modèle de diffusion gaussien cependant, qui est limité quand il s'agit de décrire des configurations de tissus complexes à l'intérieur d'un voxel, par exemple quand plusieurs faisceaux de fibres se croisent. Dès lors, on a cherché ces dernières années à développer des techniques qui ne reposent pas sur un modèle a priori, afin de décrire de manière plus précise le déplacement des molécules d'eau, et dépasser les limitations du modèle tensoriel. La plupart de ces techniques, dites à haute résolution angulaire, sollicitent un temps d'acquisition généralement long, et mettent en jeu des problèmes de reconstruction non triviaux. Dans la première partie de cette thèse, nous décrivons la structure microscopique des tissus de la matière blanche du cerveau, et présentons la physique de formation des images en IRM de diffusion. Nous faisons un état de l'art des méthodes de reconstruction, et des techniques d'acquisition proposées à ce jour. En ce qui concerne les méthodes de reconstruction, nous faisons la distinction suivant qu'elles soient basées sur un modèle ou non. La première contribution de cette thèse est liée à la reconstruction paramétrique du signal de diffusion dans une base de fonctions continues. Cette contribution fait suite à une méthode proposée récemment, appelée transformée de Fourier sphérique, et y apporte une modification pour une reconstruction continue. Nous réduisons de façon significative la dimension de la base, tout en décrivant aussi bien le signal de diffusion. Nous donnons également l'expression de l'opérateur de régularisation de Laplace en fonction des coefficients dans cette base, afin de limiter l'impact du bruit sur la reconstruction. La seconde contribution est également liée à la reconstruction du signal de diffusion, et à la fonction de distribution d'orientation, dans un contexte d'application clinique. Nous proposons une méthode de reconstruction en temps réel basée sur le filtre de Kalman pour la probabilité marginale de diffusion angulaire. Nous développons un algorithme pour détecter les mouvements du patient, de façon précise et avec une grande sensibilité, et ce sans surcoût, comparé aux systèmes utilisant une camera et des algorithmes de vision robotique. Les deux dernières contributions présentées dans cette thèse sont liées aux techniques d'acquisition en IRM de diffusion, en particulier pour l'élaboration de schémas d'acquisition sur une ou plusieurs sphères dans l'espace de Fourier. Nous présentons d'abord une méthode géométrique pour placer des points dans l'espace de Fourier sur plusieurs sphères, en optimisant la couverture angulaire sur chacune des sphères, mais également de façon globale. Puis nous cherchons à établir un lien entre le schéma d'acquisition et la base de fonctions utilisée pour la reconstruction, et nous proposons en particulier une méthode pour élaborer un protocole d'acquisition qui permette de minimiser le nombre de conditionnement, pour la reconstruction dans la base des harmoniques sphériques, et dans la base de Fourier sphérique modifiée, proposée dans cette thèse. En conclusion de cette étude sur l'acquisition, nous pensons que l'élaboration du schéma d'échantillonnage doit être motivée à la fois pour répondre aux contraintes physiques du scanner, et par le choix de la base dans laquelle le signal sera reconstruit. Ces nouveaux schémas d'échantillonnage sont disponibles au téléchargement sur mon site internet.

Published
2012

49. Diffantom: Whole-brain diffusion MRI phantoms derived from real datasets of the human connectome project

Author

Esteban Sanz-Dranguet, Oscar, Caruyer, Emmanuel, Daducci, Alessandro, Bach-Cuadra, Meritxell, Ledesma Carbayo, María Jesús, Santos Lleo, Andres de, Esteban Sanz-Dranguet, Oscar, Caruyer, Emmanuel, Daducci, Alessandro, Bach-Cuadra, Meritxell, Ledesma Carbayo, María Jesús, and Santos Lleo, Andres de

Abstract

Diffantom is a whole-brain diffusion MRI (dMRI) phantom publicly available through the Dryad Digital Repository (doi:10.5061/dryad.4p080). The dataset contains two single-shell dMRI images, along with the corresponding gradient information, packed following the BIDS standard (Brain Imaging Data Structure, Gorgolewski et al., 2015). The released dataset is designed for the evaluation of the impact of susceptibility distortions and benchmarking existing correction methods. In this Data Report we also release the software instruments involved in generating diffantoms, so that researchers are able to generate new phantoms derived from different subjects, and apply these data in other applications like investigating diffusion sampling schemes, the assessment of dMRI processing methods, the simulation of pathologies and imaging artifacts, etc. In summary, Diffantom is intended for unit testing of novel methods, cross-comparison of established methods, and integration testing of partial or complete processing flows to extract connectivity networks from dMRI.

Published
2016

50. Tractography-based connectomes are dominated by false-positive connections

Author

Maier-Hein, Klaus H., primary, Neher, Peter, additional, Houde, Jean-Christophe, additional, Côté, Marc-Alexandre, additional, Garyfallidis, Eleftherios, additional, Zhong, Jidan, additional, Chamberland, Maxime, additional, Yeh, Fang-Cheng, additional, Lin, Ying-Chia, additional, Ji, Qing, additional, Reddick, Wilburn E., additional, Glass, John O., additional, Chen, David Qixiang, additional, Feng, Yuanjing, additional, Gao, Chengfeng, additional, Wu, Ye, additional, Ma, Jieyan, additional, Renjie, H, additional, Li, Qiang, additional, Westin, Carl-Fredrik, additional, Deslauriers-Gauthier, Samuel, additional, González, J. Omar Ocegueda, additional, Paquette, Michael, additional, St-Jean, Samuel, additional, Girard, Gabriel, additional, Rheault, François, additional, Sidhu, Jasmeen, additional, Tax, Chantal M.W., additional, Guo, Fenghua, additional, Mesri, Hamed Y., additional, Dávid, Szabolcs, additional, Froeling, Martijn, additional, Heemskerk, Anneriet M., additional, Leemans, Alexander, additional, Boré, Arnaud, additional, Pinsard, Basile, additional, Bedetti, Christophe, additional, Desrosiers, Matthieu, additional, Brambati, Simona, additional, Doyon, Julien, additional, Sarica, Alessia, additional, Vasta, Roberta, additional, Cerasa, Antonio, additional, Quattrone, Aldo, additional, Yeatman, Jason, additional, Khan, Ali R., additional, Hodges, Wes, additional, Alexander, Simon, additional, Romascano, David, additional, Barakovic, Muhamed, additional, Auría, Anna, additional, Esteban, Oscar, additional, Lemkaddem, Alia, additional, Thiran, Jean-Philippe, additional, Cetingul, H. Ertan, additional, Odry, Benjamin L., additional, Mailhe, Boris, additional, Nadar, Mariappan S., additional, Pizzagalli, Fabrizio, additional, Prasad, Gautam, additional, Villalon-Reina, Julio E., additional, Galvis, Justin, additional, Thompson, Paul M., additional, Requejo, Francisco De Santiago, additional, Laguna, Pedro Luque, additional, Lacerda, Luis Miguel, additional, Barrett, Rachel, additional, Dell’Acqua, Flavio, additional, Catani, Marco, additional, Petit, Laurent, additional, Caruyer, Emmanuel, additional, Daducci, Alessandro, additional, Dyrby, Tim B., additional, Holland-Letz, Tim, additional, Hilgetag, Claus C., additional, Stieltjes, Bram, additional, and Descoteaux, Maxime, additional

Published
2016
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