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ORCIDJérôme Lapuyade-Lahorgue
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- affiliation: Université de Rouen, France
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2020 – today
- 2024
[j12]Aghiles Kebaili
, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes. Neurocomputing 606: 128360 (2024)- [c7]Thibaud Brochet, Kangfu Han, Jiale Cheng, Fenqiang Zhao, Jérôme Lapuyade-Lahorgue, Su Ruan, Yi-Fang Tu, Sheng-Che Hung, Gang Li:
Neonatal Hypoxic Ischemic Encephalopathy Severity Grading Using Multimodal Swin Transformer. ISBI 2024: 1-4 - [c6]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes. ISBI 2024: 1-5 - [i6]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes. CoRR abs/2406.05421 (2024) - [i5]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes. CoRR abs/2406.11659 (2024) - 2023
- [j11]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan:
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. J. Imaging 9(4): 81 (2023) - [c5]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Hua Li, Pierre Vera, Pierre Decazes, Su Ruan:
Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy. IPTA 2023: 1-5 - [i4]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan:
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. CoRR abs/2307.13125 (2023) - [i3]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks. CoRR abs/2311.10472 (2023) - 2022
- [j10]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 24(4): 436 (2022) - [j9]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Alexandre Huat, Sébastien Thureau, David Pasquier, Isabelle Gardin, Romain Modzelewski, David Gibon, Juliette Thariat, Vincent Grégoire, Pierre Vera, Su Ruan:
Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 2022, 24, 436. Entropy 24(5): 685 (2022) - [i2]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
A Quantitative Comparison between Shannon and Tsallis Havrda Charvat Entropies Applied to Cancer Outcome Prediction. CoRR abs/2203.11943 (2022) - 2021
- [i1]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Sébastien Bougleux, Mathieu Salaün, Su Ruan:
Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy. CoRR abs/2104.05450 (2021) - 2020
- [c4]Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Sébastien Bougleux, Mathieu Salaün, Su Ruan:
Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy. IPTA 2020: 1-5
2010 – 2019
- 2019
- [c3]Haigen Hu, Pierre Decazes, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
Gaussian-based Spatial Hybrid Distances for Detection and Segmentation of Lymphoid Lesions in 3D PET Images. CISP-BMEI 2019: 1-5 - 2018
- [j8]Yuntao Yu, Pierre Decazes, Jérôme Lapuyade-Lahorgue, Isabelle Gardin, Pierre Vera, Su Ruan:
Semi-automatic lymphoma detection and segmentation using fully conditional random fields. Comput. Medical Imaging Graph. 70: 1-7 (2018) - [c2]Jierui Zha, Pierre Decazes, Jérôme Lapuyade, Abderrahim Elmoataz, Su Ruan:
3D lymphoma detection in PET-CT images with supervoxel and CRFs. IPTA 2018: 1-5 - 2017
- [j7]Jérôme Lapuyade-Lahorgue, Jing-Hao Xue, Su Ruan:
Segmenting Multi-Source Images Using Hidden Markov Fields With Copula-Based Multivariate Statistical Distributions. IEEE Trans. Image Process. 26(7): 3187-3195 (2017) - 2014
- [j6]Ilkka Norros, Pirkko Kuusela, Jérôme Lapuyade-Lahorgue, Maurizio Naldi, Mika Sirvio:
Repairable Systems With Dependent Components: Stochastic Process Techniques and Models. IEEE Trans. Reliab. 63(4): 899-912 (2014) - 2012
- [j5]Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski:
Unsupervised segmentation of hidden semi-Markov non-stationary chains. Signal Process. 92(1): 29-42 (2012) - 2011
- [j4]Pierre Lanchantin, Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski:
Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise. Signal Process. 91(2): 163-175 (2011) - [c1]Jérôme Lapuyade-Lahorgue, Ali Mohammad-Djafari:
Nearest neighbors and correlation dimension for dimensionality estimation. Application to factor analysis of real biological time series data. ESANN 2011 - 2010
- [j3]Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski:
Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise. Signal Process. 90(11): 2899-2910 (2010) - [j2]Nicolas Brunel, Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski:
Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas. IEEE Trans. Autom. Control. 55(2): 338-349 (2010)
2000 – 2009
- 2008
- [j1]Pierre Lanchantin, Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski:
Unsupervised segmentation of triplet Markov chains hidden with long-memory noise. Signal Process. 88(5): 1134-1151 (2008)
Coauthor Index
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