Unsupervised segmentation of triplet Markov chains hidden with long-memory noise. - Pierre Lanchantin; Jérôme Lapuyade-Lahorgue; Wojciech Pieczynski (Signal Process., 2008)

Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise. - Jérôme Lapuyade-Lahorgue; Wojciech Pieczynski (Signal Process., 2010)

Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas. - Nicolas Brunel; Jérôme Lapuyade-Lahorgue; Wojciech Pieczynski (IEEE Trans. Autom. Control., 2010)

Nearest neighbors and correlation dimension for dimensionality estimation. Application to factor analysis of real biological time series data. - Jérôme Lapuyade-Lahorgue; Ali Mohammad-Djafari (ESANN, 2011)

Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise. - Pierre Lanchantin; Jérôme Lapuyade-Lahorgue; Wojciech Pieczynski (Signal Process., 2011)

Unsupervised segmentation of hidden semi-Markov non-stationary chains. - Jérôme Lapuyade-Lahorgue; Wojciech Pieczynski (Signal Process., 2012)

Repairable Systems With Dependent Components: Stochastic Process Techniques and Models. - Ilkka Norros; Pirkko Kuusela; Jérôme Lapuyade-Lahorgue; Maurizio Naldi; Mika Sirvio (IEEE Trans. Reliab., 2014)

Segmenting Multi-Source Images Using Hidden Markov Fields With Copula-Based Multivariate Statistical Distributions. - Jérôme Lapuyade-Lahorgue; Jing-Hao Xue; Su Ruan (IEEE Trans. Image Process., 2017)

3D lymphoma detection in PET-CT images with supervoxel and CRFs. - Jierui Zha; Pierre Decazes; Jérôme Lapuyade; Abderrahim Elmoataz; Su Ruan (IPTA, 2018)

Semi-automatic lymphoma detection and segmentation using fully conditional random fields. - Yuntao Yu; Pierre Decazes; Jérôme Lapuyade-Lahorgue; Isabelle Gardin; Pierre Vera; Su Ruan (Comput. Medical Imaging Graph., 2018)

Gaussian-based Spatial Hybrid Distances for Detection and Segmentation of Lymphoid Lesions in 3D PET Images. - Haigen Hu; Pierre Decazes; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (CISP-BMEI, 2019)

Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy. - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Sébastien Bougleux; Mathieu Salaün; Su Ruan (IPTA, 2020)

Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy. - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Sébastien Bougleux; Mathieu Salaün; Su Ruan (CoRR, 2021)

Deep Learning Based Radiomics to Predict Treatment Response Using Multi-datasets. - 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 (MICAD, 2022)

Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 2022, 24, 436. - 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 (Entropy, 2022)

A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (Entropy, 2022)

Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy. - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Hua Li 003; Pierre Vera; Pierre Decazes; Su Ruan (IPTA, 2023)

End-to-End Autoencoding Architecture for the Simultaneous Generation of Medical Images and Corresponding Segmentation Masks. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (MICAD, 2023)

Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Su Ruan (J. Imaging, 2023)

Neonatal Hypoxic Ischemic Encephalopathy Severity Grading Using Multimodal Swin Transformer. - Thibaud Brochet; Kangfu Han; Jiale Cheng; Fenqiang Zhao; Jérôme Lapuyade-Lahorgue; Su Ruan; Yi-Fang Tu; Sheng-Che Hung; Gang Li 001 (ISBI, 2024)

3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (ISBI, 2024)

Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (Neurocomputing, 2024)

AMM-Diff: Adaptive Multi-Modality Diffusion Network for Missing Modality Imputation. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (ISBI, 2025)

Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation. - Aghiles Kebaili; Jérôme Lapuyade-Lahorgue; Pierre Vera; Su Ruan (Comput. Medical Imaging Graph., 2025)