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ORCIDConstance Fourcade
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2020 – today
- 2023
[j1]Alessa Hering
, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjölund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich:
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. IEEE Trans. Medical Imaging 42(3): 697-712 (2023)- 2022
- [c6]Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mathilde Colombié, Pascal Jézéquel, Mario Campone, Mathieu Rubeaux, Nicolas Normand:
Influence of inputs for bone lesion segmentation in longitudinal 18F-FDG PET/CT imaging studies. EMBC 2022: 4736-4739 - 2021
- [c5]Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Pascal Jézéquel, Mario Campone, Nicolas Normand, Mathieu Rubeaux:
Comparison between threshold-based and deep learning-based bone segmentation on whole-body CT images. Medical Imaging: Computer-Aided Diagnosis 2021 - [c4]Gianmarco Santini, Yvon Nzoughet Obame, Constance Fourcade, Noémie Moreau, Mathieu Rubeaux:
Automatic classification of benign and malignant kidney masses using radiomics. A retrospective study exploiting the KiTS19 dataset. Medical Imaging: Image Processing 2021 - [i2]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:
Deformable Image Registration with Deep Network Priors: a Study on Longitudinal PET Images. CoRR abs/2111.11873 (2021) - [i1]Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Huaqi Qiu, Zeju Li, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich:
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. CoRR abs/2112.04489 (2021) - 2020
- [c3]Noémie Moreau, Caroline Rousseau, Constance Fourcade, Gianmarco Santini, Ludovic Ferrer, Marie Lacombe, Camille Guillerminet, Mario Campone, Mathilde Colombié, Mathieu Rubeaux, Nicolas Normand:
Deep learning approaches for bone and bone lesion segmentation on 18FDG PET/CT imaging in the context of metastatic breast cancer*. EMBC 2020: 1532-1535 - [c2]Constance Fourcade, Ludovic Ferrer, Gianmarco Santini, Noémie Moreau, Caroline Rousseau, Marie Lacombe, Camille Guillerminet, Mathilde Colombié, Mario Campone, Diana Mateus, Mathieu Rubeaux:
Combining Superpixels and Deep Learning Approaches to Segment Active Organs in Metastatic Breast Cancer PET Images*. EMBC 2020: 1536-1539 - [c1]Constance Fourcade, Mathieu Rubeaux, Diana Mateus:
Using Elastix to Register Inhale/Exhale Intrasubject Thorax CT: A Unsupervised Baseline to the Task 2 of the Learn2Reg Challenge. MICCAI (Challenges) 2020: 100-105
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