Deep evidential fusion with uncertainty quantification and reliability learning for multimodal medical image segmentation. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (Inf. Fusion, 2025)

Generation of super-resolution for medical image via a self-prior guided Mamba network with edge-aware constraint. - Ji, Zexin; Zou, Beiji; Kui, Xiaoyan; Li, Hua; Vera, Pierre; Ruan, Su (Pattern Recognit. Lett., 2025)

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

Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention. - Ghazouani, Fethi; Vera, Pierre; Ruan, Su (Int. J. Comput. Assist. Radiol. Surg., 2024)

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

A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods. - Huang, Ling; Ruan, Su; Xing, Yucheng; Feng, Mengling (Medical Image Anal., 2024)

Self-prior Guided Mamba-UNet Networks for Medical Image Super-Resolution. - Ji, Zexin; Zou, Beiji; Kui, Xiaoyan; Vera, Pierre; Ruan, Su (2024)

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

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

Deform-Mamba Network for MRI Super-Resolution. - Ji, Zexin; Zou, Beiji; Kui, Xiaoyan; Vera, Pierre; Ruan, Su (2024)

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

Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes. - Kebaili, Aghiles; Lapuyade-Lahorgue, Jérôme; Vera, Pierre; Ruan, Su (CoRR, 2024)

Deform-Mamba Network for MRI Super-Resolution. - Ji, Zexin; Zou, Beiji; Kui, Xiaoyan; Vera, Pierre; Ruan, Su (CoRR, 2024)

Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution. - Ji, Zexin; Zou, Beiji; Kui, Xiaoyan; Vera, Pierre; Ruan, Su (CoRR, 2024)

AutoPETIII: The Tracer Frontier. What Frontier? - Mesbah, Zacharia; Mottay, Léo; Modzelewski, Romain; Decazes, Pierre; Hapdey, Sébastien; Ruan, Su; Thureau, Sébastien (CoRR, 2024)

EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers. - Huang, Ling; Xing, Yucheng; Lin, Qika; Ruan, Su; Feng, Mengling (CoRR, 2024)

A literature survey of MR-based brain tumor segmentation with missing modalities. - Zhou, Tongxue; Ruan, Su; Hu, Haigen (Comput. Medical Imaging Graph., 2023)

Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning. - Zhou, Tongxue; Noeuveglise, Alexandra; Modzelewski, Romain; Ghazouani, Fethi; Thureau, Sébastien; Fontanilles, Maxime; Ruan, Su (Comput. Medical Imaging Graph., 2023)

Semi-supervised multiple evidence fusion for brain tumor segmentation. - Huang, Ling; Ruan, Su; Denoeux, Thierry (Neurocomputing, 2023)

Application of belief functions to medical image segmentation: A review. - Huang, Ling; Ruan, Su; Denoeux, Thierry (Inf. Fusion, 2023)

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

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

One-shot Learning for DLBCL Segmentation in Whole Body PET/CT Images. - Zhang, Lixin; Sun, Yulun; Decazes, Pierre; Ruan, Su; Guo, Yu; Yu, Hui (2023)

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

Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning. - Zhou, Tongxue; Noeuveglise, Alexandra; Modzelewski, Romain; Ghazouani, Fethi; Thureau, Sébastien; Fontanilles, Maxime; Ruan, Su (CoRR, 2023)

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

Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (CoRR, 2023)

A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods. - Huang, Ling; Ruan, Su; Xing, Yucheng; Feng, Mengling (CoRR, 2023)

End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks. - Kebaili, Aghiles; Lapuyade-Lahorgue, Jérôme; Vera, Pierre; Ruan, Su (CoRR, 2023)

Multi-task multi-scale learning for outcome prediction in 3D PET images. - Amyar, Amine; Modzelewski, Romain; Vera, Pierre; Morard, Vincent; Ruan, Su (Comput. Biol. Medicine, 2022)

Multi-scale feature similarity-based weakly supervised lymphoma segmentation in PET/CT images. - Huang, Zhengshan; Guo, Yu; Zhang, Ning; Huang, Xian; Decazes, Pierre; Becker, Stéphanie; Ruan, Su (Comput. Biol. Medicine, 2022)

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

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

Lymphoma segmentation from 3D PET-CT images using a deep evidential network. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (Int. J. Approx. Reason., 2022)

Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction. - Amyar, Amine; Modzelewski, Romain; Vera, Pierre; Morard, Vincent; Ruan, Su (J. Imaging, 2022)

A Tri-Attention fusion guided multi-modal segmentation network. - Zhou, Tongxue; Ruan, Su; Vera, Pierre; Canu, Stéphane (Pattern Recognit., 2022)

Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images. - Hu, Haigen; Shen, Leizhao; Guan, Qiu; Li, Xiaoxin; Zhou, Qianwei; Ruan, Su (Pattern Recognit., 2022)

Missing Data Imputation via Conditional Generator and Correlation Learning for Multimodal Brain Tumor Segmentation. - Zhou, Tongxue; Vera, Pierre; Canu, Stéphane; Ruan, Su (Pattern Recognit. Lett., 2022)

Prediction of Brain Tumor Recurrence Location Based on Kullback-Leibler Divergence and Nonlinear Correlation Learning. - Zhou, Tongxue; Noeuveglise, Alexandra; Ghazouani, Fethi; Modzelewski, Romain; Thureau, Sébastien; Fontanilles, Maxime; Ruan, Su (2022)

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

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT. - Andrearczyk, Vincent; Oreiller, Valentin; Abobakr, Moamen; Akhavanallaf, Azadeh; Balermpas, Panagiotis; Boughdad, Sarah; Capriotti, Leo; Castelli, Joël; Rest, Catherine Cheze Le; Decazes, Pierre; Correia, Ricardo; El-Habashy, Dina; et al. (2022)

Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. - Huang, Ling; Denoeux, Thierry; Vera, Pierre; Ruan, Su (2022)

Lymphoma segmentation from 3D PET-CT images using a deep evidential network. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (CoRR, 2022)

Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images. - Amyar, Amine; Modzelewski, Romain; Vera, Pierre; Morard, Vincent; Ruan, Su (CoRR, 2022)

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

Application of belief functions to medical image segmentation: A review. - Huang, Ling; Ruan, Su (CoRR, 2022)

A novel adversarial learning strategy for medical image classification. - Fan, Zong; Zhang, Xiaohui; Gasienica, Jacob A.; Potts, Jennifer; Ruan, Su; Thorstad, Wade; Gay, Hiram; Wang, Xiaowei; Li, Hua (CoRR, 2022)

Evidence fusion with contextual discounting for multi-modality medical image segmentation. - Huang, Ling; Denoeux, Thierry; Vera, Pierre; Ruan, Su (CoRR, 2022)

A novel systematic approach for cancer treatment prognosis and its applications in oropharyngeal cancer with microRNA biomarkers. - He, Shenghua; Lian, Chunfeng; Thorstad, Wade; Gay, Hiram; Zhao, Yujie; Ruan, Su; Wang, Xiaowei; Li, Hua (Bioinform., 2021)

Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (Neurocomputing, 2021)

Automatic COVID-19 CT segmentation using U-Net integrated spatial and channel attention mechanism. - Zhou, Tongxue; Canu, Stéphane; Ruan, Su (Int. J. Imaging Syst. Technol., 2021)

Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (IEEE Trans. Image Process., 2021)

Evidential Segmentation of 3D PET/CT Images. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (2021)

Covid-19 Classification with Deep Neural Network and Belief Functions. - Huang, Ling; Ruan, Su; Denoeux, Thierry (2021)

Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation. - Huang, Ling; Ruan, Su; Denoeux, Thierry (2021)

A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (2021)

Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation. - Huang, Ling; Denoeux, Thierry; Tonnelet, David; Decazes, Pierre; Ruan, Su (2021)

Deep learning-based multi-class COVID-19 classification with x-ray images. - Fan, Zong; He, Shenghua; Ruan, Su; Wang, Xiaowei; Li, Hua (2021)

Covid-19 classification with deep neural network and belief functions. - Huang, Ling; Ruan, Su; Denoeux, Thierry (CoRR, 2021)

Belief function-based semi-supervised learning for brain tumor segmentation. - Huang, Ling; Ruan, Su; Denoeux, Thierry (CoRR, 2021)

3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (CoRR, 2021)

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

Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (CoRR, 2021)

Evidential segmentation of 3D PET/CT images. - Huang, Ling; Ruan, Su; Decazes, Pierre; Denoeux, Thierry (CoRR, 2021)

Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation. - Huang, Ling; Denoeux, Thierry; Tonnelet, David; Decazes, Pierre; Ruan, Su (CoRR, 2021)

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics. - Yousefirizi, Fereshteh; Decazes, Pierre; Amyar, Amine; Ruan, Su; Saboury, Babak; Rahmim, Arman (CoRR, 2021)

A Tri-attention Fusion Guided Multi-modal Segmentation Network. - Zhou, Tongxue; Ruan, Su; Vera, Pierre; Canu, Stéphane (CoRR, 2021)

Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (CoRR, 2021)

Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images. - Hu, Haigen; Shen, Leizhao; Guan, Qiu; Li, Xiaoxin; Zhou, Qianwei; Ruan, Su (CoRR, 2021)

Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation. - Amyar, Amine; Modzelewski, Romain; Li, Hua; Ruan, Su (Comput. Biol. Medicine, 2020)

Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation. - Zhou, Tongxue; Canu, Stéphane; Ruan, Su (Comput. Medical Imaging Graph., 2020)

Incoherent dictionary learning via mixed-integer programming and hybrid augmented Lagrangian. - Liu, Yuan; Canu, Stéphane; Honeine, Paul; Ruan, Su (Digit. Signal Process., 2020)

Corrections to "Medical Image Synthesis With Deep Convolutional Adversarial Networks". - Nie, Dong; Trullo, Roger; Lian, Jun; Wang, Li; Petitjean, Caroline; Ruan, Su; Wang, Qian; Shen, Dinggang (IEEE Trans. Biomed. Eng., 2020)

RADIOGAN: Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images. - Amyar, Amine; Ruan, Su; Vera, Pierre; Decazes, Pierre; Modzelewski, Romain (2020)

3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (2020)

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

SegTHOR: Segmentation of Thoracic Organs at Risk in CT images. - Lambert, Zoé; Petitjean, Caroline; Dubray, Bernard; Ruan, Su (2020)

Deep Disentangled Representation Learning of Pet Images for Lymphoma Outcome Prediction. - Guo, Yu; Decazes, Pierre; Becker, Stéphanie; Li, Hua; Ruan, Su (2020)

A Multi-Modality Fusion Network Based on Attention Mechanism for Brain Tumor Segmentation. - Zhou, Tongxue; Ruan, Su; Guo, Yu; Canu, Stéphane (2020)

Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy. - Hu, Haigen; Shen, Leizhao; Zhou, Tongxue; Decazes, Pierre; Vera, Pierre; Ruan, Su (2020)

Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (2020)

Weakly Supervised PET Tumor Detection Using Class Response. - Amyar, Amine; Modzelewski, Romain; Vera, Pierre; Morard, Vincent; Ruan, Su (CoRR, 2020)

RADIOGAN: Deep Convolutional Conditional Generative adversarial Network To Generate PET Images. - Amyar, Amine; Ruan, Su; Vera, Pierre; Decazes, Pierre; Modzelewski, Romain (CoRR, 2020)

Brain tumor segmentation with missing modalities via latent multi-source correlation representation. - Zhou, Tongxue; Canu, Stéphane; Vera, Pierre; Ruan, Su (CoRR, 2020)

An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism. - Zhou, Tongxue; Canu, Stéphane; Ruan, Su (CoRR, 2020)

A review: Deep learning for medical image segmentation using multi-modality fusion. - Zhou, Tongxue; Ruan, Su; Canu, Stéphane (CoRR, 2020)

A review: Deep learning for medical image segmentation using multi-modality fusion. - Zhou, Tongxue; Ruan, Su; Canu, Stéphane (Array, 2019)

Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy. - Hu, Haigen; Decazes, Pierre; Vera, Pierre; Li, Hua; Ruan, Su (Int. J. Comput. Assist. Radiol. Surg., 2019)

Adaptive kernelized evidential clustering for automatic 3D tumor segmentation in FDG-PET images. - Wang, Fan; Lian, Chunfeng; Vera, Pierre; Ruan, Su (Multim. Syst., 2019)

Mixed Integer Programming For Sparse Coding: Application to Image Denoising. - Liu, Yuan; Canu, Stéphane; Honeine, Paul; Ruan, Su (IEEE Trans. Computational Imaging, 2019)

Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Li, Hua; Vera, Pierre (IEEE Trans. Image Process., 2019)

A Background-based Data Enhancement Method for Lymphoma Segmentation in 3D PET Images. - Hu, Haigen; Du, Chao; Guan, Qiu; Zhou, Qianwei; Vera, Pierre; Ruan, Su (2019)

A Prior Knowledge Intergrated Scheme for Detection and Segmentation of Lymphomas in 3D PET Images based on DBSCAN and GAs. - Hu, Haigen; Du, Chao; Decazes, Pierre; Vera, Pierre; Ruan, Su (2019)

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

Deep Learning Model Integrating Dilated Convolution and Deep Supervision for Brain Tumor Segmentation in Multi-parametric MRI. - Zhou, Tongxue; Ruan, Su; Hu, Haigen; Canu, Stéphane (2019)

Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, SegTHOR@ISBI 2019, April 8, 2019 (CEUR-WS.org, 2019)

SegTHOR: Segmentation of Thoracic Organs at Risk in CT images. - Lambert, Zoé; Petitjean, Caroline; Dubray, Bernard; Ruan, Su (CoRR, 2019)

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

A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images. - Wu, Jian; Mazur, Thomas R.; Ruan, Su; Lian, Chunfeng; Daniel, Nalini; Lashmett, Hilary; Ochoa, Laura; Zoberi, Imran; Anastasio, Mark A.; Gach, H. Michael; Mutic, Sasa; Thomas, Maria; et al. (Medical Image Anal., 2018)

Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Li, Hua; Vera, Pierre (IEEE Trans. Biomed. Eng., 2018)

Medical Image Synthesis with Deep Convolutional Adversarial Networks. - Nie, Dong; Trullo, Roger; Lian, Jun; Wang, Li; Petitjean, Caroline; Ruan, Su; Wang, Qian; Shen, Dinggang (IEEE Trans. Biomed. Eng., 2018)

Feature selection and classification using multiple kernel learning for brain tumor segmentation. - Boughattas, Naouel; Berar, Maxime; Hamrouni, Kamel; Ruan, Su (2018)

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

Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion. - Lian, Chunfeng; Li, Hua; Vera, Pierre; Ruan, Su (2018)

Active learning with noise modeling for medical image annotation. - Wu, Jian; Ruan, Su; Lian, Chunfeng; Mutic, Sasa; Anastasio, Mark A.; Li, Hua (2018)

Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method. - Wu, Jian; Ruan, Su; Mazur, Thomas R.; Daniel, Nalini; Lashmett, Hilary; Ochoa, Laura; Zoberi, Imran; Lian, Chunfeng; Gach, H. Michael; Mutic, Sasa; Thomas, Maria; Anastasio, Mark A.; et al. (2018)

K-SVD with a Real ℓ0 Optimization: Application to Image Denoising. - Liu, Yuan; Canu, Stéphane; Honeine, Paul; Ruan, Su (2018)

Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier. - Desbordes, Paul; Ruan, Su; Modzelewski, Romain; Sébastien, Vauclin; Vera, Pierre; Gardin, Isabelle (Comput. Medical Imaging Graph., 2017)

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

Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Guo, Yu; Vera, Pierre (2017)

Fully automated esophagus segmentation with a hierarchical deep learning approach. - Trullo, Roger; Petitjean, Caroline; Nie, Dong; Shen, Dinggang; Ruan, Su (2017)

Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields. - Trullo, Roger; Petitjean, Caroline; Ruan, Su; Dubray, Bernard; Nie, Dong; Shen, Dinggang (2017)

Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Li, Hua; Vera, Pierre (2017)

3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs. - Yu, Yuntao; Decazes, Pierre; Gardin, Isabelle; Vera, Pierre; Ruan, Su (2017)

Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures. - Trullo, Roger; Petitjean, Caroline; Nie, Dong; Shen, Dinggang; Ruan, Su (2017)

Medical Image Synthesis with Context-Aware Generative Adversarial Networks. - Nie, Dong; Trullo, Roger; Lian, Jun; Petitjean, Caroline; Ruan, Su; Wang, Qian; Shen, Dinggang (2017)

Une véritable approche $\ell_0$ pour l'apprentissage de dictionnaire. - Liu, Yuan; Canu, Stéphane; Honeine, Paul; Ruan, Su (CoRR, 2017)

Multilabel statistical shape prior for image segmentation. - Grosgeorge, Damien; Petitjean, Caroline; Ruan, Su (IET Image Process., 2016)

Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Jardin, Fabrice; Vera, Pierre (Medical Image Anal., 2016)

Dissimilarity Metric Learning in the Belief Function Framework. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry (IEEE Trans. Fuzzy Syst., 2016)

Joint Feature Transformation and Selection Based on Dempster-Shafer Theory. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry (2016)

Comparison of 2D and 3D region-based deformable models and random walker methods for PET segmentation. - Gosse, Kevin; Jehan-Besson, Stéphanie; Lecellier, François; Ruan, Su (2016)

Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Li, Hua; Vera, Pierre (2016)

Medical Image Synthesis with Context-Aware Generative Adversarial Networks. - Nie, Dong; Trullo, Roger; Petitjean, Caroline; Ruan, Su; Shen, Dinggang (CoRR, 2016)

Robust feature selection to predict tumor treatment outcome. - Mi, Hongmei; Petitjean, Caroline; Dubray, Bernard; Vera, Pierre; Ruan, Su (Artif. Intell. Medicine, 2015)

Right ventricle segmentation from cardiac MRI: A collation study. - Petitjean, Caroline; Zuluaga, Maria A.; Bai, Wenjia; Dacher, Jean-Nicolas; Grosgeorge, Damien; Caudron, Jérôme; Ruan, Su; Ayed, Ismail Ben; Cardoso, Manuel Jorge; Chen, Hsiang-Chou; Jimenez-Carretero, Daniel; Ledesma-Carbayo, María J.; et al. (Medical Image Anal., 2015)

Joint tumor growth prediction and tumor segmentation on therapeutic follow-up PET images. - Mi, Hongmei; Petitjean, Caroline; Vera, Pierre; Ruan, Su (Medical Image Anal., 2015)

An evidential classifier based on feature selection and two-step classification strategy. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry (Pattern Recognit., 2015)

Modelling and Tracking of Deformable Structures in Medical Images. - Ettaïeb, Saïd; Hamrouni, Kamel; Ruan, Su (2015)

Outcome prediction in tumour therapy based on Dempster-Shafer theory. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Vera, Pierre (2015)

Segmentation of pelvic organs at risk using superpixels and graph diffusion in prostate radiotherapy. - Guinin, Maxime; Ruan, Su; Nkhali, Lamyaa; Dubray, Bernard; Massoptier, Laurent; Gardin, Isabelle (2015)

Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy. - Lian, Chunfeng; Ruan, Su; Denoeux, Thierry; Li, Hua; Vera, Pierre (2015)

Factor analysis-based approach for early uptake automatic quantification of breast cancer by 18F-FDG PET images sequence. - Ketata, Ines; Sallemi, Lamia; Morain-Nicolier, Frédéric; Slima, Mohamed Ben; Cochet, Alexandre; Chtourou, Khalil; Ruan, Su; Hamida, Ahmed Ben (Biomed. Signal Process. Control., 2014)

Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm. - Onoma, D. P.; Ruan, Su; Thureau, Sébastien; Nkhali, Lamyaa; Modzelewski, Romain; Monnehan, G. A.; Vera, Pierre; Gardin, Isabelle (Comput. Medical Imaging Graph., 2014)

Dealing with uncertainty and imprecision in image segmentation using belief function theory. - Lelandais, Benoît; Gardin, Isabelle; Mouchard, Laurent; Vera, Pierre; Ruan, Su (Int. J. Approx. Reason., 2014)

Eikonal-based region growing for efficient clustering. - Buyssens, Pierre; Gardin, Isabelle; Ruan, Su; Elmoataz, Abderrahim (Image Vis. Comput., 2014)

Fusion of multi-tracer PET images for dose painting. - Lelandais, Benoît; Ruan, Su; Denoeux, Thierry; Vera, Pierre; Gardin, Isabelle (Medical Image Anal., 2014)

Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET. - Mi, Hongmei; Petitjean, Caroline; Dubray, Bernard; Vera, Pierre; Ruan, Su (IEEE Trans. Medical Imaging, 2014)

Advanced approach for PET breast cancer segmentation based on FAMIS methodology. - Ketata, Ines; Sallemi, Lamia; Slima, Mohamed Ben; Hamida, Ahmed Ben; Morain-Nicolier, Frédéric; Ruan, Su; Cochet, Alexandre; Chtourou, Khalil (2014)

Brain tumor segmentation from multiple MRI sequences using multiple kernel learning. - Boughattas, Naouel; Berar, Maxime; Hamrouni, Kamel; Ruan, Su (2014)

Myocardium segmentation using a priori knowledge of shape and a spatial relation. - Ettaïeb, Saïd; Hamrouni, Kamel; Ruan, Su (2014)

3D automated lymphoma segmentation in PET images based on cellular automata. - Desbordes, Paul; Petitjean, Caroline; Ruan, Su (2014)

Joint segmentation of right and left cardiac ventricles using multi-label graph cut. - Grosgeorge, Damien; Petitjean, Caroline; Ruan, Su (2014)

Prostate cancer segmentation from multiparametric MRI based on fuzzy Bayesian model. - Guo, Yu; Ruan, Su; Walker, Paul; Feng, Yuanming (2014)

Automatic lung tumor segmentation on PET images based on random walks and tumor growth model. - Mi, Hongmei; Petitjean, Caroline; Dubray, Bernard; Vera, Pierre; Ruan, Su (2014)

Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation. - Ettaïeb, Saïd; Hamrouni, Kamel; Ruan, Su (2014)

Nonrigid Medical Image Registration Based on Mesh Deformation Constraints. - Lin, Xiangbo; Ruan, Su; Qiu, Tianshuang; Guo, Dongmei (Comput. Math. Methods Medicine, 2013)

Esophagus Segmentation from 3D CT Data Using Skeleton Prior-Based Graph Cut. - Grosgeorge, Damien; Petitjean, Caroline; Dubray, Bernard; Ruan, Su (Comput. Math. Methods Medicine, 2013)

Graph cut segmentation with a statistical shape model in cardiac MRI. - Grosgeorge, Damien; Petitjean, Caroline; Dacher, Jean-Nicolas; Ruan, Su (Comput. Vis. Image Underst., 2013)

Predicting lung tumor evolution during radiotherapy from PET images using a patient specific model. - Mi, Hongmei; Petitjean, Caroline; Ruan, Su; Vera, Pierre; Dubray, Bernard (2013)

Signal Separation with A Priori Knowledge Using Sparse Representation. - Guo, Yu; Ruan, Su (2013)

Using Belief Function Theory to Deal with Uncertainties and Imprecisions in Image Processing. - Lelandais, Benoît; Gardin, Isabelle; Mouchard, Laurent; Vera, Pierre; Ruan, Su (2012)

Analyzing the intrinsic relations between the diffusion and fluid deformable registration methods. - Lin, Xiangbo; Ruan, Su (2012)

3D random walk based segmentation for lung tumor delineation in PET imaging. - Onoma, D. P.; Ruan, Su; Gardin, Isabelle; Monnehan, G. A.; Modzelewski, Romain; Vera, Pierre (2012)

Segmentation of Biological Target Volumes on Multi-tracer PET Images Based on Information Fusion for Achieving Dose Painting in Radiotherapy. - Lelandais, Benoît; Gardin, Isabelle; Mouchard, Laurent; Vera, Pierre; Ruan, Su (2012)

A priori knowledge based frequency-domain quantification of prostate Magnetic Resonance Spectroscopy. - Guo, Yu; Ruan, Su; Landré, Jérôme; Walker, Paul (Biomed. Signal Process. Control., 2011)

Kernel feature selection to fuse multi-spectral MRI images for brain tumor segmentation. - Zhang, Nan; Ruan, Su; Lebonvallet, Stéphane; Liao, Qingmin; Zhu, Yuemin (Comput. Vis. Image Underst., 2011)

Image fusion for following-up brain tumor evolution. - Ruan, Su; Zhang, Nan; Liao, Qingmin; Zhu, Yuemin (2011)

A topology preserving non-rigid registration algorithm with integration shape knowledge to segment brain subcortical structures from MRI images. - Lin, Xiangbo; Qiu, Tianshuang; Morain-Nicolier, Frédéric; Ruan, Su (Pattern Recognit., 2010)

Brain Magnetic Resonance Image. - Ruan, Su; Lebonvallet, Stéphane (Stud. Inform. Univ., 2010)

A Sparse Representation Method for Magnetic Resonance Spectroscopy Quantification. - Guo, Yu; Ruan, Su; Landré, Jérôme; Constans, Jean-Marc (IEEE Trans. Biomed. Eng., 2010)

An automatic method of brain tumor segmentation from MRI volume based on the symmetry of brain and level set method. - Li, Xiaobing; Qiu, Tianshuang; Lebonvallet, Stéphane; Ruan, Su (2010)

Fusion and classification of multi-source images by SVM with selected features in a kernel space. - Ruan, Su; Zhang, Nan; Lebonvallet, Stéphane; Liao, Qingmin; Zhu, Yue Min (2010)

Graph cut segmentation technique for MRI brain tumor extraction. - Chen, Victor; Ruan, Su (2010)

Binary pattern matching from a local dissimilarity measure. - Morain-Nicolier, Frédéric; Landré, Jérôme; Ruan, Su (2010)

Spectrum separation of Magnetic Resonance Spectroscopy based on sparse representation. - Guo, Yu; Ruan, Su; Millon, Gilles; Constans, Jean-Marc (2009)

Ornamental Letters Image Classification Using Local Dissimilarity Maps. - Landré, Jérôme; Morain-Nicolier, Frédéric; Ruan, Su (2009)

Multi-kernel SVM based classification for brain tumor segmentation of MRI multi-sequence. - Zhang, Nan; Ruan, Su; Lebonvallet, Stéphane; Liao, Qingmin; Zhu, Yuemin (2009)

Binary-image comparison with local-dissimilarity quantification. - Baudrier, Étienne; Nicolier, Frédéric; Millon, Gilles; Ruan, Su (Pattern Recognit., 2008)

Segmentation of Brain Internal Structures Automatically Using Non-rigid Registration with Simultaneous Intensity and Geometric Match. - Lin, Xiangbo; Qiu, Tianshuang; Ruan, Su; Morain-Nicolier, Frédéric (2008)

Fuzzy kappa for the agreement measure of fuzzy classifications. - Dou, Weibei; Ren, Yuan; Wu, Qian; Ruan, Su; Chen, Yanping; Bloyet, Daniel; Constans, Jean-Marc (Neurocomputing, 2007)

A framework of fuzzy information fusion for the segmentation of brain tumor tissues on MR images. - Dou, Weibei; Ruan, Su; Chen, Yanping; Bloyet, Daniel; Constans, Jean-Marc (Image Vis. Comput., 2007)

Tumor Segmentation from a Multispectral MRI Images by Using Support Vector Machine Classification. - Ruan, Su; Lebonvallet, Stéphane; Merabet, Abderrahim; Constans, Jean-Marc (2007)

MRI segmentation using multifractal analysis and MRF models. - Ruan, Su; Bailleul, Jonathan (2007)

Automated tumor segmentation using level set methods. - Lebonvallet, Stéphane; Khatchadourian, Sonia; Ruan, Su (2007)

A fast binary-image comparison method with local-dissimilarity quantification. - Baudrier, Étienne; Millon, Gilles; Nicolier, Frédéric; Ruan, Su (2006)

A Smart Identification Card System Using Facial Biometric: From Architecture to Application. - Peng, Kun; Chen, Liming; Ruan, Su (2006)

A novel scheme of face verification using active appearance models. - Peng, Kun; Chen, Liming; Ruan, Su (2005)

Histogram-Based Generation Method of Membership Function for Extracting Features of Brain Tissues on MRI Images. - Dou, Weibei; Ren, Yuan; Chen, Yanping; Ruan, Su; Bloyet, Daniel; Constans, Jean-Marc (2005)

A Robust and Efficient Algorithm for Eye Detection on Gray Intensity Face. - Peng, Kun; Chen, Liming; Ruan, Su; Kukharev, Georgy (2005)

A new similarity measure using hausdorff distance map. - Baudrier, Étienne; Millon, Gilles; Nicolier, Frédéric; Ruan, Su (2004)

Segmentation of anatomical structures from 3D brain MRI using automatically-built statistical shape models. - Bailleul, Jonathan; Ruan, Su; Bloyet, Daniel; Romaniuk, Barbara (2004)

3d medical image segmentation approach based on multi-label front propagation. - Li, Hua; Elmoataz, Abderrahim; Fadili, Jalal; Ruan, Su; Romaniuk, Barbara (2004)

A Multi-Label Front Propagation Approach for Object Segmentation. - Li, Hua; Elmoataz, Abderrahim; Fadili, Mohamed-Jalal; Ruan, Su (2004)

Segmentation based on information fusion applied to brain tissue on MRI. - Dou, Weibei; Ruan, Su; Bloyet, Daniel; Constans, Jean-Marc; Chen, Yanping (2004)

Dual Front Evolution Model and Its Application in Medical Imaging. - Li, Hua; Elmoataz, Abderrahim; Fadili, Mohamed-Jalal; Ruan, Su (2004)

Possibilistic-clustering-based MR brain image segmentation with accurate initialization. - Liao, Qingmin; Deng, Yingying; Dou, Weibei; Ruan, Su; Bloyet, Daniel (2004)

Automatic atlas-based building of point distribution model for segmentation of anatomical structures from brain MRI. - Bailleul, Jonathan; Ruan, Su; Bloyet, Daniel (2003)

Knowledge based fuzzy information fusion applied to classification of abnormal brain tissues from MRI. - Dou, Weibei; Ruan, Su; Liao, Qingmin; Bloyet, Daniel; Constans, Jean-Marc (2003)

Fuzzy Information Fusion Scheme Used to Segment Brain Tumor from MR Images. - Dou, Weibei; Ruan, Su; Liao, Qingmin; Bloyet, Daniel; Constans, Jean-Marc; Chen, Yanping (2003)

Fuzzy Markovian Segmentation in Application of Magnetic Resonance Images. - Ruan, Su; Moretti, Bruno; Fadili, Jalal; Bloyet, Daniel (Comput. Vis. Image Underst., 2002)

Cerebral magnetic resonance image segmentation using fuzzy Markov Random Fields. - Ruan, Su; Bloyet, Daniel; Revenu, Marinette; Dou, Weibei; Liao, Qingmin (2002)

On the number of clusters and the fuzziness index for unsupervised FCA application to BOLD fMRI time series. - Fadili, Mohamed-Jalal; Ruan, Su; Bloyet, Daniel; Mazoyer, Bernard (Medical Image Anal., 2001)

Knowledge-based segmentation and labeling of brain structures from MRI images. - Xue, Jing-Hao; Ruan, Su; Moretti, Bruno; Revenu, Marinette; Bloyet, Daniel (Pattern Recognit. Lett., 2001)

Segmentation of magnetic resonance images using fuzzy Markov random fields. - Ruan, Su; Moretti, Bruno; Fadili, Jalal; Bloyet, Daniel (2001)

Phantom-based performance evaluation: Application to brain segmentation from magnetic resonance images. - Moretti, Bruno; Fadili, Mohamed-Jalal; Ruan, Su; Bloyet, Daniel; Mazoyer, Bernard (Medical Image Anal., 2000)

Brain Tissue Classification of Magnetic Resonance Images Using Partial Volume Modeling. - Ruan, Su; Jaggi, Cyril; Xue, Jing-Hao; Fadili, Mohamed-Jalal; Bloyet, Daniel (IEEE Trans. Medical Imaging, 2000)

Fuzzy Modeling of Knowledge for MRI Brain Structure Segmentation. - Xue, Jing-Hao; Ruan, Su; Moretti, Bruno; Revenu, Marinette; Bloyet, Daniel; Philips, Wilfried (2000)

Unsupervised Segmentation of Three-Dimensional Brain Images. - Ruan, Su; Fadili, Mohamed-Jalal; Bloyet, Daniel; Xue, Jing-Hao (2000)

Detection of Brain Activation from MRI Data by Likelihood-Ratio Test. - Ruan, Su; Jaggi, Cyril; Constans, Jean-Marc; Bloyet, Daniel (1995)

Three-dimensional motion and reconstruction of coronary arteries from biplane cineangiography. - Ruan, Su; Bruno, Alain; Coatrieux, Jean-Louis (Image Vis. Comput., 1994)