-
Arnaud Berenbaum,
Hervé Delingette,
Aurélien Maire,
Cécile Poret,
Claire Hassen-Khodja,
Stéphane Bréant,
Christel Daniel,
Patricia Martel,
Lamiae Grimaldi,
Marie Frank,
Emmanuel Durand,
and Florent Besson.
Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project.
Applied Sciences,
13(9):5281,
May 2023.
Keyword(s): FDG PET,
artificial intelligence,
deep learning,
convolutional neural network.
@article{berenbaum:hal-04081046,
TITLE = {{Performance of AI-Based Automated Classifications of Whole-Body FDG PET in Clinical Practice: The CLARITI Project}},
AUTHOR = {Berenbaum, Arnaud and Delingette, Herv{\'e} and Maire, Aur{\'e}lien and Poret, C{\'e}cile and Hassen-Khodja, Claire and Br{\'e}ant, St{\'e}phane and Daniel, Christel and Martel, Patricia and Grimaldi, Lamiae and Frank, Marie and Durand, Emmanuel and Besson, Florent},
url-hal= {https://inria.hal.science/hal-04081046},
JOURNAL = {{Applied Sciences}},
PUBLISHER = {{MDPI}},
VOLUME = {13},
NUMBER = {9},
PAGES = {5281},
YEAR = {2023},
MONTH = May,
DOI = {10.3390/app13095281},
KEYWORDS = {FDG PET ; artificial intelligence ; deep learning ; convolutional neural network},
HAL_ID = {hal-04081046},
HAL_VERSION = {v1},
}
-
Hind Dadoun,
Hervé Delingette,
Anne-Laure Rousseau,
Eric de Kerviler,
and Nicholas Ayache.
Deep Clustering for Abdominal Organ Classification in US imaging.
Journal of Medical Imaging,
2023.
Keyword(s): ultrasound imaging,
representation learning,
deep clustering,
semi-supervised learning.
@article{dadoun:hal-03773082,
TITLE = {{Deep Clustering for Abdominal Organ Classification in US imaging}},
AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
url-hal= {https://inria.hal.science/hal-03773082},
JOURNAL = {{Journal of Medical Imaging}},
PUBLISHER = {{SPIE Digital Library}},
YEAR = {2023},
KEYWORDS = {ultrasound imaging ; representation learning ; deep clustering ; semi-supervised learning},
PDF = {https://inria.hal.science/hal-03773082v3/file/soumission_jmi_dadoun_vf.pdf},
HAL_ID = {hal-03773082},
HAL_VERSION = {v3},
}
-
Nicolas Guigui,
Nina Miolane,
and Xavier Pennec.
Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats.
Foundations and Trends in Machine Learning,
16(3):329-493,
February 2023.
Keyword(s): Riemannian Geometry,
Geometric Statistics,
Python Library.
@article{guigui:hal-03766900,
TITLE = {{Introduction to Riemannian Geometry and Geometric Statistics: from basic theory to implementation with Geomstats}},
AUTHOR = {Guigui, Nicolas and Miolane, Nina and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-03766900},
JOURNAL = {{Foundations and Trends in Machine Learning}},
PUBLISHER = {{Now Publishers}},
VOLUME = {16},
NUMBER = {3},
PAGES = {329-493},
YEAR = {2023},
MONTH = Feb,
DOI = {10.1561/2200000098},
KEYWORDS = {Riemannian Geometry ; Geometric Statistics ; Python Library},
PDF = {https://inria.hal.science/hal-03766900v2/file/main-now.pdf},
HAL_ID = {hal-03766900},
HAL_VERSION = {v2},
}
-
Philipp Harms,
Peter W. Michor,
Xavier Pennec,
and Stefan Sommer.
Geometry of Sample Spaces.
Differential Geometry and its Applications,
2023.
Note: 29 pages, 1 figure.
@article{harms:hal-02972385,
TITLE = {{Geometry of Sample Spaces}},
AUTHOR = {Harms, Philipp and Michor, Peter W. and Pennec, Xavier and Sommer, Stefan},
url-hal= {https://inria.hal.science/hal-02972385},
NOTE = {29 pages, 1 figure},
JOURNAL = {{Differential Geometry and its Applications}},
PUBLISHER = {{Elsevier}},
YEAR = {2023},
HAL_ID = {hal-02972385},
HAL_VERSION = {v1},
}
-
Yann Thanwerdas and Xavier Pennec.
O(n)-invariant Riemannian metrics on SPD matrices.
Linear Algebra and its Applications,
661:163-201,
March 2023.
Keyword(s): 53B20,
Symmetric Positive Definite matrices,
Riemannian geometry,
Invariance under orthogonal transformations,
Families of metrics,
Log-Euclidean metric,
Affine-invariant metric,
Bures-Wasserstein metric,
Kernel metrics.
@article{thanwerdas:hal-03338601,
TITLE = {{O(n)-invariant Riemannian metrics on SPD matrices}},
AUTHOR = {Thanwerdas, Yann and Pennec, Xavier},
url-hal= {https://hal.science/hal-03338601},
JOURNAL = {{Linear Algebra and its Applications}},
PUBLISHER = {{Elsevier}},
VOLUME = {661},
PAGES = {163-201},
YEAR = {2023},
MONTH = Mar,
DOI = {10.1016/j.laa.2022.12.009},
KEYWORDS = {53B20 ; Symmetric Positive Definite matrices ; Riemannian geometry ; Invariance under orthogonal transformations ; Families of metrics ; Log-Euclidean metric ; Affine-invariant metric ; Bures-Wasserstein metric ; Kernel metrics},
PDF = {https://hal.science/hal-03338601v3/file/LAA_YT_XP_O_n_invariant_metrics_v3%20%282%29.pdf},
HAL_ID = {hal-03338601},
HAL_VERSION = {v3},
}
-
Paul Tourniaire,
Marius Ilie,
Paul Hofman,
Nicholas Ayache,
and Hervé Delingette.
MS-CLAM: Mixed Supervision for the classification and localization of tumors in Whole Slide Images.
Medical Image Analysis,
2023.
Keyword(s): Digital Pathology,
Mixed Supervision,
Deep Learning,
Camelyon16,
DigestPath2019.
@article{tourniaire:hal-03972289,
TITLE = {{MS-CLAM: Mixed Supervision for the classification and localization of tumors in Whole Slide Images}},
AUTHOR = {Tourniaire, Paul and Ilie, Marius and Hofman, Paul and Ayache, Nicholas and Delingette, Herv{\'e}},
url-hal= {https://inria.hal.science/hal-03972289},
JOURNAL = {{Medical Image Analysis}},
PUBLISHER = {{Elsevier}},
YEAR = {2023},
KEYWORDS = {Digital Pathology ; Mixed Supervision ; Deep Learning ; Camelyon16 ; DigestPath2019},
PDF = {https://inria.hal.science/hal-03972289/file/article_MedIA_hal_version.pdf},
HAL_ID = {hal-03972289},
HAL_VERSION = {v1},
}
-
Zihao Wang,
Zhifei Xu,
Jiayi He,
Herve Delingette,
and Jun Fan.
Long Short-Term Memory Neural Equalizer.
IEEE Transactions on Signal and Power Integrity,
2:13-22,
2023.
@article{wang:hal-04042921,
TITLE = {{Long Short-Term Memory Neural Equalizer}},
AUTHOR = {Wang, Zihao and Xu, Zhifei and He, Jiayi and Delingette, Herve and Fan, Jun},
url-hal= {https://hal.inria.fr/hal-04042921},
JOURNAL = {{IEEE Transactions on Signal and Power Integrity}},
VOLUME = {2},
PAGES = {13-22},
YEAR = {2023},
DOI = {10.1109/TSIPI.2023.3242855},
HAL_ID = {hal-04042921},
HAL_VERSION = {v1},
}
-
Nicolas Cedilnik and Jean-Marc Peyrat.
Weighted tissue thickness.
In FIMH 2023 - 12th International Conference On Functional Imaging And Modeling Of The Heart,
Lecture Notes in Computer Science,
Lyon, France,
June 2023.
Springer.
Keyword(s): Thickness,
Thickness measurements,
Medical image analysis.
@inproceedings{cedilnik:hal-04111276,
TITLE = {{Weighted tissue thickness}},
AUTHOR = {Cedilnik, Nicolas and Peyrat, Jean-Marc},
url-hal= {https://inria.hal.science/hal-04111276},
BOOKTITLE = {{FIMH 2023 - 12th International Conference On Functional Imaging And Modeling Of The Heart}},
ADDRESS = {Lyon, France},
PUBLISHER = {{Springer}},
SERIES = {Lecture Notes in Computer Science},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Thickness ; Thickness measurements ; Medical image analysis},
PDF = {https://inria.hal.science/hal-04111276/file/article.pdf},
HAL_ID = {hal-04111276},
HAL_VERSION = {v1},
}
-
Hind Dadoun,
Hervé Delingette,
Anne-Laure Rousseau,
Eric de Kerviler,
and Nicholas Ayache.
Joint representation learning from french radiological reports and ultrasound images.
In IEEE ISBI 2023 - International Symposium on Biomedical Imaging,
Cartagena de Indias, Colombia,
April 2023.
IEEE.
Keyword(s): multimodal learning deep clustering natural language processing ultrasound examinations kidneys,
multimodal learning,
deep clustering,
natural language processing,
ultrasound examinations,
kidneys.
@inproceedings{dadoun:hal-03984528,
TITLE = {{Joint representation learning from french radiological reports and ultrasound images}},
AUTHOR = {Dadoun, Hind and Delingette, Herv{\'e} and Rousseau, Anne-Laure and de Kerviler, Eric and Ayache, Nicholas},
url-hal= {https://inria.hal.science/hal-03984528},
BOOKTITLE = {{IEEE ISBI 2023 - International Symposium on Biomedical Imaging}},
ADDRESS = {Cartagena de Indias, Colombia},
ORGANIZATION = {{IEEE}},
YEAR = {2023},
MONTH = Apr,
KEYWORDS = {multimodal learning deep clustering natural language processing ultrasound examinations kidneys ; multimodal learning ; deep clustering ; natural language processing ; ultrasound examinations ; kidneys},
PDF = {https://inria.hal.science/hal-03984528/file/HIND_DADOUN_ISBI_2023.pdf},
HAL_ID = {hal-03984528},
HAL_VERSION = {v1},
}
-
Morten Pedersen,
Xavier Pennec,
and Stefan Sommer.
Tangent phylogenetic PCA.
In Scandinavian Conference on Image Analysis 2023,
Levi Ski Resort (Lapland), Finland,
April 2023.
@inproceedings{pedersen:hal-03842847,
TITLE = {{Tangent phylogenetic PCA}},
AUTHOR = {Pedersen, Morten and Pennec, Xavier and Sommer, Stefan},
url-hal= {https://inria.hal.science/hal-03842847},
BOOKTITLE = {{Scandinavian Conference on Image Analysis 2023}},
ADDRESS = {Levi Ski Resort (Lapland), Finland},
YEAR = {2023},
MONTH = Apr,
PDF = {https://inria.hal.science/hal-03842847/file/2208.12730.pdf},
HAL_ID = {hal-03842847},
HAL_VERSION = {v1},
}
-
Yingyu Yang and Maxime Sermesant.
Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation.
In FIMH 2023 - The 12th International Conference on Functional Imaging and Modeling of The Heart,
Lyon, France,
June 2023.
Keyword(s): Motion Estimation Echocardiography Polyaffine Transformation,
Motion Estimation,
Echocardiography,
Polyaffine Transformation.
@inproceedings{yang:hal-04109721,
TITLE = {{Unsupervised Polyaffine Transformation Learning for Echocardiography Motion Estimation}},
AUTHOR = {Yang, Yingyu and Sermesant, Maxime},
url-hal= {https://inria.hal.science/hal-04109721},
BOOKTITLE = {{FIMH 2023 - The 12th International Conference on Functional Imaging and Modeling of The Heart}},
ADDRESS = {Lyon, France},
YEAR = {2023},
MONTH = Jun,
KEYWORDS = {Motion Estimation Echocardiography Polyaffine Transformation ; Motion Estimation ; Echocardiography ; Polyaffine Transformation},
PDF = {https://inria.hal.science/hal-04109721/file/Unsupervised_Polyaffine_Motion_Model_for_Echocardiography_Analysis__final_-2.pdf},
HAL_ID = {hal-04109721},
HAL_VERSION = {v1},
}
-
Safaa Al-Ali,
Jordi Llopis-Lorente,
Maria Teresa Mora,
Maxime Sermesant,
Beatriz Trénor,
and Irene Balelli.
A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment.
Note: Working paper or preprint,
May 2023.
Keyword(s): Causal discovery,
Drug safety,
Ions channel,
TdP risk.
@unpublished{alali:hal-04105144,
TITLE = {{A causal discovery approach for streamline ion channels selection to improve drug-induced TdP risk assessment}},
AUTHOR = {Al-Ali, Safaa and Llopis-Lorente, Jordi and Mora, Maria Teresa and Sermesant, Maxime and Tr{\'e}nor, Beatriz and Balelli, Irene},
url-hal= {https://hal.science/hal-04105144},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = May,
KEYWORDS = {Causal discovery ; Drug safety ; Ions channel ; TdP risk},
PDF = {https://hal.science/hal-04105144/file/Draft_CMSB_Sept_2023-2.pdf},
HAL_ID = {hal-04105144},
HAL_VERSION = {v1},
}
-
Irene Balelli,
Aude Sportisse,
Francesco Cremonesi,
Pierre-Alexandre Mattei,
and Marco Lorenzi.
Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models.
Note: Working paper or preprint,
April 2023.
Keyword(s): Missing data,
Federated learning,
Federated pre-processing,
Variational autoencoders,
Deep Learning.
@unpublished{balelli:hal-04069795,
TITLE = {{Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models}},
AUTHOR = {Balelli, Irene and Sportisse, Aude and Cremonesi, Francesco and Mattei, Pierre-Alexandre and Lorenzi, Marco},
url-hal= {https://hal.science/hal-04069795},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Apr,
KEYWORDS = {Missing data ; Federated learning ; Federated pre-processing ; Variational autoencoders ; Deep Learning},
PDF = {https://hal.science/hal-04069795/file/main_MICCAI.pdf},
HAL_ID = {hal-04069795},
HAL_VERSION = {v1},
}
-
Blanche Buet and Xavier Pennec.
Flagfolds.
Note: Working paper or preprint,
2023.
@unpublished{buet:hal-04112465,
TITLE = {{Flagfolds}},
AUTHOR = {Buet, Blanche and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04112465},
NOTE = {working paper or preprint},
YEAR = {2023},
HAL_ID = {hal-04112465},
HAL_VERSION = {v1},
}
-
Quentin Clairon,
Chloé Pasin,
Irene Balelli,
Rodolphe Thiébaut,
and Mélanie Prague.
Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach.
Note: Working paper or preprint,
January 2023.
Keyword(s): Dynamic population models,
Ordinary differential equations,
Optimal control theory,
Mechanistic models,
Nonlinear mixed effects models,
Clinical trial analysis.
@unpublished{clairon:hal-03335826,
TITLE = {{Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: An optimal control approach}},
AUTHOR = {Clairon, Quentin and Pasin, Chlo{\'e} and Balelli, Irene and Thi{\'e}baut, Rodolphe and Prague, M{\'e}lanie},
url-hal= {https://hal.science/hal-03335826},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Jan,
KEYWORDS = {Dynamic population models ; Ordinary differential equations ; Optimal control theory ; Mechanistic models ; Nonlinear mixed effects models ; Clinical trial analysis},
PDF = {https://hal.science/hal-03335826v2/file/Manuscript_Estimation_NLMEODE_via_OCA_CompStat%20%281%29.pdf},
HAL_ID = {hal-03335826},
HAL_VERSION = {v2},
}
-
Francesco Cremonesi,
Marc Vesin,
Sergen Cansiz,
Yannick Bouillard,
Irene Balelli,
Lucia Innocenti,
Santiago Silva,
Samy-Safwan Ayed,
Riccardo Taiello,
Laetita Kameni,
Richard Vidal,
Fanny Orlhac,
Christophe Nioche,
Nathan Lapel,
Bastien Houis,
Romain Modzelewski,
Olivier Humbert,
Melek Önen,
and Marco Lorenzi.
Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications.
Note: Working paper or preprint,
April 2023.
Keyword(s): Machine learning,
Biomedical Application,
Healthcare,
Federated Learning Framework.
@unpublished{cremonesi:hal-04081557,
TITLE = {{Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications}},
AUTHOR = {Cremonesi, Francesco and Vesin, Marc and Cansiz, Sergen and Bouillard, Yannick and Balelli, Irene and Innocenti, Lucia and Silva, Santiago and Ayed, Samy-Safwan and Taiello, Riccardo and Kameni, Laetita and Vidal, Richard and Orlhac, Fanny and Nioche, Christophe and Lapel, Nathan and Houis, Bastien and Modzelewski, Romain and Humbert, Olivier and {\"O}nen, Melek and Lorenzi, Marco},
url-hal= {https://inria.hal.science/hal-04081557},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Apr,
KEYWORDS = {Machine learning ; Biomedical Application ; Healthcare ; Federated Learning Framework},
PDF = {https://inria.hal.science/hal-04081557/file/fedbiomed_paper-5.pdf},
HAL_ID = {hal-04081557},
HAL_VERSION = {v1},
}
-
Etrit Haxholli and Marco Lorenzi.
Faster Training and Improved Performance of Diffusion Models via Parallel Score Matching.
Note: Working paper or preprint,
March 2023.
@unpublished{haxholli:hal-04032669,
TITLE = {{Faster Training and Improved Performance of Diffusion Models via Parallel Score Matching}},
AUTHOR = {Haxholli, Etrit and Lorenzi, Marco},
url-hal= {https://hal.inria.fr/hal-04032669},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = Mar,
HAL_ID = {hal-04032669},
HAL_VERSION = {v1},
}
-
Tom Szwagier and Xavier Pennec.
Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem.
Note: Working paper or preprint,
May 2023.
Keyword(s): Flag manifolds,
Riemannian logarithm,
Orthogonal alignment,
Procrustes analysis,
Flag manifolds Riemannian logarithm Orthogonal alignment Procrustes analysis,
Flag manifolds.
@unpublished{szwagier:hal-04100534,
TITLE = {{Rethinking the Riemannian Logarithm on Flag Manifolds as an Orthogonal Alignment Problem}},
AUTHOR = {Szwagier, Tom and Pennec, Xavier},
url-hal= {https://inria.hal.science/hal-04100534},
NOTE = {working paper or preprint},
YEAR = {2023},
MONTH = May,
KEYWORDS = {Flag manifolds ; Riemannian logarithm ; Orthogonal alignment ; Procrustes analysis ; Flag manifolds Riemannian logarithm Orthogonal alignment Procrustes analysis ; Flag manifolds},
PDF = {https://inria.hal.science/hal-04100534/file/GSI-119.pdf},
HAL_ID = {hal-04100534},
HAL_VERSION = {v1},
}