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2020 – today
- 2022
[c4]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
- [c3]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 - 2020
- [c2]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 - [c1]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
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