Search Results - "Fick, Rutger"

MAPL: Tissue microstructure estimation using Laplacian-regularized MAP-MRI and its application to HCP data by Fick, Rutger H.J., Wassermann, Demian, Caruyer, Emmanuel, Deriche, Rachid

“…The recovery of microstructure-related features of the brain's white matter is a current challenge in diffusion MRI. To robustly estimate these important…”
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The Dmipy Toolbox: Diffusion MRI Multi-Compartment Modeling and Microstructure Recovery Made Easy by Fick, Rutger H. J., Wassermann, Demian, Deriche, Rachid

“…Non-invasive estimation of brain microstructure features using diffusion MRI (dMRI) - known as Microstructure Imaging - has become an increasingly diverse and…”
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Interpretable HER2 scoring by evaluating clinical guidelines through a weakly supervised, constrained deep learning approach by Pham, Manh-Dan, Balezo, Guillaume, Tilmant, Cyprien, Petit, Stéphanie, Salmon, Isabelle, Hadj, Saïma Ben, Fick, Rutger H.J.

“…The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection…”
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Non-parametric graphnet-regularized representation of dMRI in space and time by Fick, Rutger H.J., Petiet, Alexandra, Santin, Mathieu, Philippe, Anne-Charlotte, Lehericy, Stephane, Deriche, Rachid, Wassermann, Demian

“…•qτ-dMRI signal representation without making biophysical assumptions.•Non-parametric, time-dependent reconstruction of the diffusion signal and EAP.•Effective…”
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Mitosis domain generalization in histopathology images — The MIDOG challenge by Aubreville, Marc, Stathonikos, Nikolas, Bertram, Christof A., Klopfleisch, Robert, ter Hoeve, Natalie, Ciompi, Francesco, Wilm, Frauke, Marzahl, Christian, Donovan, Taryn A., Maier, Andreas, Breen, Jack, Ravikumar, Nishant, Chung, Youjin, Park, Jinah, Nateghi, Ramin, Pourakpour, Fattaneh, Fick, Rutger H.J., Ben Hadj, Saima, Jahanifar, Mostafa, Shephard, Adam, Dexl, Jakob, Wittenberg, Thomas, Kondo, Satoshi, Lafarge, Maxime W., Koelzer, Viktor H., Liang, Jingtang, Wang, Yubo, Long, Xi, Liu, Jingxin, Razavi, Salar, Khademi, April, Yang, Sen, Wang, Xiyue, Erber, Ramona, Klang, Andrea, Lipnik, Karoline, Bolfa, Pompei, Dark, Michael J., Wasinger, Gabriel, Veta, Mitko, Breininger, Katharina

“…The density of mitotic figures (MF) within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor…”
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Sparse Reconstruction Challenge for diffusion MRI: Validation on a physical phantom to determine which acquisition scheme and analysis method to use? by Ning, Lipeng, Laun, Frederik, Gur, Yaniv, DiBella, Edward V.R., Deslauriers-Gauthier, Samuel, Megherbi, Thinhinane, Ghosh, Aurobrata, Zucchelli, Mauro, Menegaz, Gloria, Fick, Rutger, St-Jean, Samuel, Paquette, Michael, Aranda, Ramon, Descoteaux, Maxime, Deriche, Rachid, O’Donnell, Lauren, Rathi, Yogesh

“…•The outcome of the SPArse Reconstruction Challenge in MICCAI 2014 is presented.•A total of 16 diffusion-MRI reconstruction algorithms from 9 teams were…”
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Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi‐group comparison by Ferizi, Uran, Scherrer, Benoit, Schneider, Torben, Alipoor, Mohammad, Eufracio, Odin, Fick, Rutger H.J., Deriche, Rachid, Nilsson, Markus, Loya‐Olivas, Ana K., Rivera, Mariano, Poot, Dirk H.J., Ramirez‐Manzanares, Alonso, Marroquin, Jose L., Rokem, Ariel, Pötter, Christian, Dougherty, Robert F., Sakaie, Ken, Wheeler‐Kingshott, Claudia, Warfield, Simon K., Witzel, Thomas, Wald, Lawrence L., Raya, José G., Alexander, Daniel C.

“…A large number of mathematical models have been proposed to describe the measured signal in diffusion‐weighted (DW) magnetic resonance imaging (MRI). However,…”
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Enabling Collagen Quantification on HE-Stained Slides through Stain Deconvolution and Restained HE-HES by Balezo, Guillaume, Bertram, Christof A., Tilmant, Cyprien, Petit, Stephanie, Hadj, Saima Ben, Fick, Rutger H. J.

“…In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by…”
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Multi Tissue Modelling of Diffusion MRI Signal Reveals Volume Fraction Bias by Frigo, Matteo, Fick, Rutger H. J., Zucchelli, Mauro, Deslauriers-Gauthier, Samuel, Deriche, Rachid

“…This paper highlights a systematic bias in white matter tissue microstructure modelling via diffusion MRI that is due to the common, yet inaccurate, assumption…”
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Reducing the number of samples in spatiotemporal dMRI acquisition design by Filipiak, Patryk, Fick, Rutger, Petiet, Alexandra, Santin, Mathieu, Philippe, Anne‐Charlotte, Lehericy, Stephane, Ciuciu, Philippe, Deriche, Rachid, Wassermann, Demian

“…Purpose Acquisition time is a major limitation in recovering brain white matter microstructure with diffusion magnetic resonance imaging. The aim of this paper…”
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On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: Chronicles of the MEMENTO challenge by De Luca, Alberto, Ianus, Andrada, Leemans, Alexander, Palombo, Marco, Shemesh, Noam, Zhang, Hui, Alexander, Daniel C., Nilsson, Markus, Froeling, Martijn, Biessels, Geert-Jan, Zucchelli, Mauro, Frigo, Matteo, Albay, Enes, Sedlar, Sara, Alimi, Abib, Deslauriers-Gauthier, Samuel, Deriche, Rachid, Fick, Rutger, Afzali, Maryam, Pieciak, Tomasz, Bogusz, Fabian, Aja-Fernández, Santiago, Özarslan, Evren, Jones, Derek K., Chen, Haoze, Jin, Mingwu, Zhang, Zhijie, Wang, Fengxiang, Nath, Vishwesh, Parvathaneni, Prasanna, Morez, Jan, Sijbers, Jan, Jeurissen, Ben, Fadnavis, Shreyas, Endres, Stefan, Rokem, Ariel, Garyfallidis, Eleftherios, Sanchez, Irina, Prchkovska, Vesna, Rodrigues, Paulo, Landman, Bennet A., Schilling, Kurt G.

“…Diffusion MRI (dMRI) has become an invaluable tool to assess the microstructural organization of brain tissue. Depending on the specific acquisition settings,…”
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TUMORAL AWARE DEEP LEARNING ALGORITHM FOR AUTOMATIC KI67 SCORING by Bertrand, Capucine, Lang, Solène Chan, Petit, Stéphanie S., Villa, Irène, Fick, Rutger, Hadj, Saima Ben

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Can AI predict epithelial lesion categories via automated analysis of cervical biopsies: The TissueNet challenge? by Loménie, Nicolas, Bertrand, Capucine, Fick, Rutger H.J., Ben Hadj, Saima, Tayart, Brice, Tilmant, Cyprien, Farré, Isabelle, Azdad, Soufiane Z., Dahmani, Samy, Dequen, Gilles, Feng, Ming, Xu, Kele, Li, Zimu, Prevot, Sophie, Bergeron, Christine, Bataillon, Guillaume, Devouassoux-Shisheboran, Mojgan, Glaser, Claire, Delaune, Agathe, Valmary-Degano, Séverine, Bertheau, Philippe

“…The French Society of Pathology (SFP) organized its first data challenge in 2020 with the help of the Health Data Hub (HDH). The organization of this event…”
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Solving the inclination sign ambiguity in three dimensional Polarized Light Imaging with a PDE-based method by Alimi, Abib, Pizzolato, Marco, Fick, Rutger H. J., Deriche, Rachid

“…Three dimensional Polarized Light Imaging (3D-PLI) is a contrast-enhancing technique that measures the spatial fiber architecture in the human postmortem brain…”
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Assessing the feasibility of estimating axon diameter using diffusion models and machine learning by Fick, Rutger H. J., Sepasian, Neda, Pizzolato, Marco, Ianus, Andrada, Deriche, Rachid

“…Axon diameter estimation has been a focus of the diffusion MRI community for the past decade. The main argument has been that while diffusion models always…”
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A Partial Label-Based Machine Learning Approach For Cervical Whole-Slide Image Classification: The Winning TissueNet Solution by Fick, Rutger H.J., Tayart, Brice, Bertrand, Capucine, Lang, Solene Chan, Rey, Tina, Ciompi, Francesco, Tilmant, Cyprien, Farre, Isabelle, Hadj, Saima Ben

“…Cervical cancer is the fourth most common cancer in women worldwide. To determine early treatment for patients, it is critical to accurately classify the…”
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Mitosis domain generalization in histopathology images -- The MIDOG challenge by Aubreville, Marc, Stathonikos, Nikolas, Bertram, Christof A, Klopleisch, Robert, ter Hoeve, Natalie, Ciompi, Francesco, Wilm, Frauke, Marzahl, Christian, Donovan, Taryn A, Maier, Andreas, Breen, Jack, Ravikumar, Nishant, Chung, Youjin, Park, Jinah, Nateghi, Ramin, Pourakpour, Fattaneh, Fick, Rutger H. J, Hadj, Saima Ben, Jahanifar, Mostafa, Rajpoot, Nasir, Dexl, Jakob, Wittenberg, Thomas, Kondo, Satoshi, Lafarge, Maxime W, Koelzer, Viktor H, Liang, Jingtang, Wang, Yubo, Long, Xi, Liu, Jingxin, Razavi, Salar, Khademi, April, Yang, Sen, Wang, Xiyue, Veta, Mitko, Breininger, Katharina

“…Medical Image Analysis 84 (2023) 102699 The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus…”
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Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology by Homeyer, André, Geißler, Christian, Schwen, Lars Ole, Zakrzewski, Falk, Evans, Theodore, Strohmenger, Klaus, Westphal, Max, Bülow, Roman David, Kargl, Michaela, Karjauv, Aray, Munné-Bertran, Isidre, Retzlaff, Carl Orge, Romero-López, Adrià, Sołtysiński, Tomasz, Plass, Markus, Carvalho, Rita, Steinbach, Peter, Lan, Yu-Chia, Bouteldja, Nassim, Haber, David, Rojas-Carulla, Mateo, Vafaei Sadr, Alireza, Kraft, Matthias, Krüger, Daniel, Fick, Rutger, Lang, Tobias, Boor, Peter, Müller, Heimo, Hufnagl, Peter, Zerbe, Norman

“…Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological…”
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Publisher Correction to: Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology by Homeyer, André, Geißler, Christian, Schwen, Lars Ole, Zakrzewski, Falk, Evans, Theodore, Strohmenger, Klaus, Westphal, Max, Bülow, Roman David, Kargl, Michaela, Karjauv, Aray, Munné-Bertran, Isidre, Retzlaff, Carl Orge, Romero-López, Adrià, Sołtysiński, Tomasz, Plass, Markus, Carvalho, Rita, Steinbach, Peter, Lan, Yu-Chia, Bouteldja, Nassim, Haber, David, Rojas-Carulla, Mateo, Vafaei Sadr, Alireza, Kraft, Matthias, Krüger, Daniel, Fick, Rutger, Lang, Tobias, Boor, Peter, Müller, Heimo, Hufnagl, Peter, Zerbe, Norman

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Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution by Portegies, J M, Fick, R H J, Sanguinetti, G R, Meesters, S P L, Girard, G, Duits, R

“…We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both…”
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