Semi-automatic lymphoma detection and segmentation using fully conditional random fields von Yu, Yuntao, Decazes, Pierre, Lapuyade-Lahorgue, Jérôme, Gardin, Isabelle, Vera, Pierre, Ruan, Su

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A framework based on hidden Markov trees for multimodal PET/CT image co‐segmentation von Hanzouli‐Ben Salah, Houda, Lapuyade‐Lahorgue, Jerome, Bert, Julien, Benoit, Didier, Lambin, Philippe, Baardwijk, Angela, Monfrini, Emmanuel, Pieczynski, Wojciech, Visvikis, Dimitris, Hatt, Mathieu

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A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction von Brochet, Thibaud, Lapuyade-Lahorgue, Jérôme, Huat, Alexandre, Thureau, Sébastien, Pasquier, David, Gardin, Isabelle, Modzelewski, Romain, Gibon, David, Thariat, Juliette, Grégoire, Vincent, Vera, Pierre, Ruan, Su

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Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review von Kebaili, Aghiles, Lapuyade-Lahorgue, Jérôme, Ruan, Su

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SPEQTACLE: An automated generalized fuzzy C‐means algorithm for tumor delineation in PET von Lapuyade‐Lahorgue, Jérôme, Visvikis, Dimitris, Pradier, Olivier, Cheze Le Rest, Catherine, Hatt, Mathieu

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Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes von Kebaili, Aghiles, Lapuyade-Lahorgue, Jérôme, Vera, Pierre, Ruan, Su

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Segmenting Multi-Source Images Using Hidden Markov Fields With Copula-Based Multivariate Statistical Distributions von Lapuyade-Lahorgue, Jérôme, Xue, Jing-Hao, Ruan, Su

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Unsupervised segmentation of triplet Markov chains hidden with long-memory noise von Lanchantin, Pierre, Lapuyade-Lahorgue, Jérôme, Pieczynski, Wojciech

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Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise von Lanchantin, Pierre, Lapuyade-Lahorgue, Jérôme, Pieczynski, Wojciech

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Segmentation of multicorrelated images with copula models and conditionally random fields von Lapuyade-Lahorgue, Jérôme, Ruan, Su

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Unsupervised segmentation of hidden semi-Markov non-stationary chains von Lapuyade-Lahorgue, Jérôme, Pieczynski, Wojciech

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Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 2022, 24 , 436 von Brochet, Thibaud, Lapuyade-Lahorgue, Jérôme, Huat, Alexandre, Thureau, Sébastien, Pasquier, David, Gardin, Isabelle, Modzelewski, Romain, Gibon, David, Thariat, Juliette, Grégoire, Vincent, Vera, Pierre, Ruan, Su

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Repairable Systems With Dependent Components: Stochastic Process Techniques and Models von Norros, Ilkka, Kuusela, Pirkko, Lapuyade-Lahorgue, Jerome, Naldi, Maurizio, Sirvio, Mika

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Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise von Lapuyade-Lahorgue, Jérôme, Pieczynski, Wojciech

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Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas von Brunel, N.J.-B., Lapuyade-Lahorgue, J., Pieczynski, W.

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Unsupervised Segmentation of Hidden Semi-Markov Non Stationary Chains von Lapuyade-Lahorgue, Jerome, Pieczynski, Wojciech

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Generation of pseudo-CT from a single MRI for PET/MR attenuation correction purposes von Monnier, Florian, Fayad, Hadi, Bert, Julian, Lapuyade-Lahorgue, Jerome, Hatt, Mathieu, Veit-Haibach, Patrick, Delso, Gaspar, Visvikis, Dimitris

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Segmentation of multicorrelated images with copula models and conditionally random fields von Lapuyade-Lahorgue, Jérôme, Ruan, Su

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SPEQTACLE: A new fuzzy clustering algorithm for fully automatic delineation of tumors in PET images von Lapuyade-Lahorgue, Jérôme, Visvikis, Dimitris, Hatt, Mathieu

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Unsupervised segmentation of new semi-Markov chains hiddenwith long dependence noise von LAPUYADE-LAHORGUE, Jérôme, PIECZYNSKI, Wojciech

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