Noémie Moreau

According to our database, Noémie Moreau authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Understanding Cell Fate Decisions with Temporal Attention.

Florian Bürger, Martim Dias Gomes, Adrián E. Granada, Noémie Moreau, Katarzyna Bozek

CoRR, March, 2026

Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps.

Kim Ouan, Noémie Moreau, Katarzyna Bozek

CoRR, March, 2026

Context-aware Skin Cancer Epithelial Cell Classification with Scalable Graph Transformers.

Lucas Sancere, Noémie Moreau, Katarzyna Bozek

CoRR, February, 2026

AMAP-APP: Efficient Segmentation and Morphometry Quantification of Fluorescent Microscopy Images of Podocytes.

Arash Fatehi, David Unnersjö-Jess, Linus Butt, Noémie Moreau, Thomas Benzing, Katarzyna Bozek

CoRR, February, 2026

2025

TransientTrack: Advanced Multi-Object Tracking and Classification of Cancer Cells with Transient Fluorescent Signals.

Florian Bürger, Martim Dias Gomes, Nica Gutu, Adrián E. Granada, Noémie Moreau, Katarzyna Bozek

CoRR, December, 2025

ActiTect: A Generalizable Machine Learning Pipeline for REM Sleep Behavior Disorder Screening through Standardized Actigraphy.

David Bertram, Anja Ophey, Sinah Röttgen, Konstantin Kufer, Gereon R. Fink, Elke Kalbe, Clint Hansen, Walter Maetzler, Maximilian Kapsecker, Lara Marie Reimer, Stephan M. Jonas, Andreas T. Damgaard, Natasha B. Bertelsen, Casper Skjærbæk, Per Borghammer, Karolien Groenewald, Pietro-Luca Ratti, Michele T. Hu, Noémie Moreau, Michael Sommerauer, Katarzyna Bozek

CoRR, November, 2025

KPIs 2024 Challenge: Advancing Glomerular Segmentation from Patch- to Slide-Level.

Ruining Deng, Tianyuan Yao, Yucheng Tang, Junlin Guo, Siqi Lu, Juming Xiong, Lining Yu, Quan Huu Cap, Pengzhou Cai, Libin Lan, Ze Zhao, Adrian Galdran, Amit Kumar, Gunjan Deotale, Dev Kumar Das, Inyoung Paik, Joonho Lee, Geongyu Lee, Yujia Chen, Wangkai Li, Zhaoyang Li, Xuege Hou, Zeyuan Wu, Shengjin Wang, Maximilian Fischer, Lars Kramer, Anghong Du, Le Zhang, Maria Sanchez Sanchez, Helena Sanchez Ulloa, David Ribalta Heredia, Carlos Perez de Arenaza Garcia, Shuoyu Xu, Bingdou He, Xinping Cheng, Tao Wang, Noémie Moreau, Katarzyna Bozek, Shubham Innani, Ujjwal Baid, Kaura Solomon Kefas, Bennett A. Landman, Yu Wang, Shilin Zhao, Mengmeng Yin, Haichun Yang, Yuankai Huo

CoRR, February, 2025

2024

GLOMNET: A Hover Deep Learning Model for Glomerulus Instance Segmentation.

Noémie Moreau, Michelle Shabani, Christoph Schell, Katarzyna Bozek

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2022

Utilisation de l'apprentissage profond pour la segmentation et la caractérisation des images TEP/TDM FDG dans le cadre du cancer du sein métastatique. (Deep learning methods to segment and characterize PET/CT images in the context of metastatic breast cancer).

Noémie Moreau

PhD thesis, 2022

Influence of inputs for bone lesion segmentation in longitudinal ¹⁸F-FDG PET/CT imaging studies.

Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mathilde Colombié, Pascal Jézéquel, Mario Campone, Mathieu Rubeaux, Nicolas Normand

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

Deformable Image Registration with Deep Network Priors: a Study on Longitudinal PET Images.

Constance Fourcade, Ludovic Ferrer, Noémie Moreau, Gianmarco Santini, Aishlinn Brennan, Caroline Rousseau, Marie Lacombe, Vincent Fleury, Mathilde Colombié, Pascal Jézéquel, Mario Campone, Mathieu Rubeaux, Diana Mateus

CoRR, 2021

Automatic classification of benign and malignant kidney masses using radiomics. A retrospective study exploiting the KiTS19 dataset.

Gianmarco Santini, Yvon Nzoughet Obame, Constance Fourcade, Noémie Moreau, Mathieu Rubeaux

Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021

Comparison between threshold-based and deep learning-based bone segmentation on whole-body CT images.

Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Pascal Jézéquel, Mario Campone, Nicolas Normand, Mathieu Rubeaux

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

2020

Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer^*.

Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mario Campone, Mathilde Colombié, Mathieu Rubeaux, Nicolas Normand

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images^*.

Constance Fourcade, Ludovic Ferrer, Gianmarco Santini, Noémie Moreau, Caroline Rousseau, Marie Lacombe, Camille Guillerminet, Mathilde Colombié, Mario Campone, Diana Mateus, Mathieu Rubeaux

Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2019

Kidney tumor segmentation using an ensembling multi-stage deep learning approach. A contribution to the KiTS19 challenge.

Gianmarco Santini, Noémie Moreau, Mathieu Rubeaux

CoRR, 2019