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

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

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

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

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

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

Self-prior Guided Mamba-UNet Networks for Medical Image Super-Resolution - Zexin Ji; Beiji Zou; Xiaoyan Kui; Pierre Vera; Su Ruan (Pattern Recognition - 27th International Conference, ICPR 2024, Kolkata, India, December 1-5, 2024, Proceedings, Part XI, 2024)

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 (IEEE International Symposium on Biomedical Imaging, ISBI 2024, Athens, Greece, May 27-30, 2024, 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 (IEEE International Symposium on Biomedical Imaging, ISBI 2024, Athens, Greece, May 27-30, 2024, 2024)

Deform-Mamba Network for MRI Super-Resolution - Zexin Ji; Beiji Zou; Xiaoyan Kui; Pierre Vera; Su Ruan (Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Marrakesh, Morocco, October 6-10, 2024, Proceedings, Part VII, 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 (CoRR, 2024)

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

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

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

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

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

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

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

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

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

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

Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Hua Li; Pierre Vera; Pierre Decazes; Su Ruan (Twelfth International Conference on Image Processing Theory, Tools and Applications, IPTA 2023, Paris, France, October 16-19, 2023, 2023)

One-shot Learning for DLBCL Segmentation in Whole Body PET/CT Images - Lixin Zhang; Yulun Sun; Pierre Decazes; Su Ruan; Yu Guo; Hui Yu (20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, April 18-21, 2023, 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 (Proceedings of 2023 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2023, Cambridge, UK, December 9-10, 2023, 2023)

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

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

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

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

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

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

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)

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

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

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

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

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

Prediction of Brain Tumor Recurrence Location Based on Kullback-Leibler Divergence and Nonlinear Correlation Learning - Tongxue Zhou; Alexandra Noeuveglise; Fethi Ghazouani; Romain Modzelewski; Sébastien Thureau; Maxime Fontanilles; Su Ruan (26th International Conference on Pattern Recognition, ICPR 2022, Montreal, QC, Canada, August 21-25, 2022, 2022)

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 (Proceedings of 2022 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2022, Leicester, UK, November 20-21, 2022, 2022)

Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT - Vincent Andrearczyk; Valentin Oreiller; Moamen Abobakr; Azadeh Akhavanallaf; Panagiotis Balermpas; Sarah Boughdad; Leo Capriotti; Joël Castelli; Catherine Cheze Le Rest; Pierre Decazes; Ricardo Correia; Dina El-Habashy; et al. (Head and Neck Tumor Segmentation and Outcome Prediction - Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings, 2022)

Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation - Ling Huang; Thierry Denoeux; Pierre Vera; Su Ruan (Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 - 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part V, 2022)

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

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

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

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

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

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

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

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

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

Evidential Segmentation of 3D PET/CT Images - Ling Huang; Su Ruan; Pierre Decazes; Thierry Denoeux (Belief Functions: Theory and Applications - 6th International Conference, BELIEF 2021, Shanghai, China, October 15-19, 2021, Proceedings, 2021)

Covid-19 Classification with Deep Neural Network and Belief Functions - Ling Huang; Su Ruan; Thierry Denoeux (BIBE 2021: The Fifth International Conference on Biological Information and Biomedical Engineering, Hangzhou, China, July 20-22, 2021, 2021)

Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation - Ling Huang; Su Ruan; Thierry Denoeux (18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, Nice, France, April 13-16, 2021, 2021)

A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation - Tongxue Zhou; Stéphane Canu; Pierre Vera; Su Ruan (Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2021, Birmingham, United Kingdom, March 25-26, 2021, 2021)

Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation - Ling Huang; Thierry Denoeux; David Tonnelet; Pierre Decazes; Su Ruan (Machine Learning in Medical Imaging - 12th International Workshop, MLMI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings, 2021)

Deep learning-based multi-class COVID-19 classification with x-ray images - Zong Fan; Shenghua He; Su Ruan; Xiaowei Wang; Hua Li (Medical Imaging 2021: Image-Guided Procedures, Robotic Interventions, and Modeling, Online, February 15-20, 2021, 2021)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

RADIOGAN: Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images - Amine Amyar; Su Ruan; Pierre Vera; Pierre Decazes; Romain Modzelewski (ICBRA 2020: 7th International Conference on Bioinformatics Research and Applications, Berlin, Germany, September, 2020, 2020)

3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint - Tongxue Zhou; Stéphane Canu; Pierre Vera; Su Ruan (25th International Conference on Pattern Recognition, ICPR 2020, Virtual Event / Milan, Italy, January 10-15, 2021, 2020)

Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy - Thibaud Brochet; Jérôme Lapuyade-Lahorgue; Sébastien Bougleux; Mathieu Salaün; Su Ruan (Tenth International Conference on Image Processing Theory, Tools and Applications, IPTA 2020, Paris, France, November 9-12, 2020, 2020)

SegTHOR: Segmentation of Thoracic Organs at Risk in CT images - Zoé Lambert; Caroline Petitjean; Bernard Dubray; Su Ruan (Tenth International Conference on Image Processing Theory, Tools and Applications, IPTA 2020, Paris, France, November 9-12, 2020, 2020)

Deep Disentangled Representation Learning of Pet Images for Lymphoma Outcome Prediction - Yu Guo; Pierre Decazes; Stéphanie Becker; Hua Li; Su Ruan (17th IEEE International Symposium on Biomedical Imaging, ISBI 2020, Iowa City, IA, USA, April 3-7, 2020, 2020)

A Multi-Modality Fusion Network Based on Attention Mechanism for Brain Tumor Segmentation - Tongxue Zhou; Su Ruan; Yu Guo; Stéphane Canu (17th IEEE International Symposium on Biomedical Imaging, ISBI 2020, Iowa City, IA, USA, April 3-7, 2020, 2020)

Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy - Haigen Hu; Leizhao Shen; Tongxue Zhou; Pierre Decazes; Pierre Vera; Su Ruan (17th IEEE International Symposium on Biomedical Imaging, ISBI 2020, Iowa City, IA, USA, April 3-7, 2020, 2020)

Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation - Tongxue Zhou; Stéphane Canu; Pierre Vera; Su Ruan (Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV, 2020)

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

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

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

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

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

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

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

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

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

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

A Background-based Data Enhancement Method for Lymphoma Segmentation in 3D PET Images - Haigen Hu; Chao Du; Qiu Guan; Qianwei Zhou; Pierre Vera; Su Ruan (2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, San Diego, CA, USA, November 18-21, 2019, 2019)

A Prior Knowledge Intergrated Scheme for Detection and Segmentation of Lymphomas in 3D PET Images based on DBSCAN and GAs - Haigen Hu; Chao Du; Pierre Decazes; Pierre Vera; Su Ruan (2019 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2019, San Diego, CA, USA, November 18-21, 2019, 2019)

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 (12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019, Suzhou, China, October 19-21, 2019, 2019)

Deep Learning Model Integrating Dilated Convolution and Deep Supervision for Brain Tumor Segmentation in Multi-parametric MRI - Tongxue Zhou; Su Ruan; Haigen Hu; Stéphane Canu (Machine Learning in Medical Imaging - 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings, 2019)

Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, SegTHOR@ISBI 2019, April 8, 2019 - Caroline Petitjean; Su Ruan; Zoé Lambert; Bernard Dubray (CEUR-WS.org, 2019)

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

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)

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

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

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

Feature selection and classification using multiple kernel learning for brain tumor segmentation - Naouel Boughattas; Maxime Berar; Kamel Hamrouni; Su Ruan (4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018, Sousse, Tunisia, March 21-24, 2018, 2018)

3D lymphoma detection in PET-CT images with supervoxel and CRFs - Jierui Zha; Pierre Decazes; Jérôme Lapuyade; Abderrahim Elmoataz; Su Ruan (Eighth International Conference on Image Processing Theory, Tools and Applications, IPTA 2018, Xi'an, China, November 7-10, 2018, 2018)

Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion - Chunfeng Lian; Hua Li; Pierre Vera; Su Ruan (15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, DC, USA, April 4-7, 2018, 2018)

Active learning with noise modeling for medical image annotation - Jian Wu; Su Ruan; Chunfeng Lian; Sasa Mutic; Mark A. Anastasio; Hua Li (15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, DC, USA, April 4-7, 2018, 2018)

Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method - Jian Wu; Su Ruan; Thomas R. Mazur; Nalini Daniel; Hilary Lashmett; Laura Ochoa; Imran Zoberi; Chunfeng Lian; H. Michael Gach; Sasa Mutic; Maria Thomas; Mark A. Anastasio; et al. (15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, DC, USA, April 4-7, 2018, 2018)

K-SVD with a Real \(l\)0 Optimization: Application to Image Denoising - Yuan Liu; Stéphane Canu; Paul Honeine; Su Ruan (28th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2018, Aalborg, Denmark, September 17-20, 2018, 2018)

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

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)

Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images - Chunfeng Lian; Su Ruan; Thierry Denoeux; Yu Guo; Pierre Vera (2017 IEEE International Conference on Image Processing, ICIP 2017, Beijing, China, September 17-20, 2017, 2017)

Fully automated esophagus segmentation with a hierarchical deep learning approach - Roger Trullo; Caroline Petitjean; Dong Nie; Dinggang Shen; Su Ruan (2017 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2017, Kuching, Malaysia, September 12-14, 2017, 2017)

Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields - Roger Trullo; Caroline Petitjean; Su Ruan; Bernard Dubray; Dong Nie; Dinggang Shen (14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, Australia, April 18-21, 2017, 2017)

Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li; Pierre Vera (14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, Australia, April 18-21, 2017, 2017)

3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs - Yuntao Yu; Pierre Decazes; Isabelle Gardin; Pierre Vera; Su Ruan (Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment - Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings, 2017)

Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures - Roger Trullo; Caroline Petitjean; Dong Nie; Dinggang Shen; Su Ruan (Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings, 2017)

Medical Image Synthesis with Context-Aware Generative Adversarial Networks - Dong Nie; Roger Trullo; Jun Lian; Caroline Petitjean; Su Ruan; Qian Wang; Dinggang Shen (Medical Image Computing and Computer Assisted Intervention - MICCAI 2017 - 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part III, 2017)

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

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

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

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

Joint Feature Transformation and Selection Based on Dempster-Shafer Theory - Chunfeng Lian; Su Ruan; Thierry Denoeux (Information Processing and Management of Uncertainty in Knowledge-Based Systems - 16th International Conference, IPMU 2016, Eindhoven, The Netherlands, June 20-24, 2016, Proceedings, Part I, 2016)

Comparison of 2D and 3D region-based deformable models and random walker methods for PET segmentation - Kevin Gosse; Stéphanie Jehan-Besson; François Lecellier; Su Ruan (Sixth International Conference on Image Processing Theory, Tools and Applications, IPTA 2016, Oulu, Finland, December 12-15, 2016, 2016)

Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li; Pierre Vera (Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II, 2016)

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

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

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

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

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

Modelling and Tracking of Deformable Structures in Medical Images - Saïd Ettaïeb; Kamel Hamrouni; Su Ruan (Image and Graphics - 8th International Conference, ICIG 2015, Tianjin, China, August 13-16, 2015, Proceedings, Part II, 2015)

Outcome prediction in tumour therapy based on Dempster-Shafer theory - Chunfeng Lian; Su Ruan; Thierry Denoeux; Pierre Vera (12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015)

Segmentation of pelvic organs at risk using superpixels and graph diffusion in prostate radiotherapy - Maxime Guinin; Su Ruan; Lamyaa Nkhali; Bernard Dubray; Laurent Massoptier; Isabelle Gardin (12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Brooklyn, NY, USA, April 16-19, 2015, 2015)

Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy - Chunfeng Lian; Su Ruan; Thierry Denoeux; Hua Li; Pierre Vera (Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5 - 9, 2015, Proceedings, Part III, 2015)

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

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

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

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

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

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

Advanced approach for PET breast cancer segmentation based on FAMIS methodology - Ines Ketata; Lamia Sallemi; Mohamed Ben Slima; Ahmed Ben Hamida; Frédéric Morain-Nicolier; Su Ruan; Alexandre Cochet; Khalil Chtourou (2014 1st International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Sousse, Tunisia, March 17-19, 2014, 2014)

Brain tumor segmentation from multiple MRI sequences using multiple kernel learning - Naouel Boughattas; Maxime Berar; Kamel Hamrouni; Su Ruan (2014 IEEE International Conference on Image Processing, ICIP 2014, Paris, France, October 27-30, 2014, 2014)

Myocardium segmentation using a priori knowledge of shape and a spatial relation - Saïd Ettaïeb; Kamel Hamrouni; Su Ruan (4th International Conference on Multimedia Computing and Systems, ICMCS 2014, Marrakech, Morocco, April 14-16, 2014, 2014)

3D automated lymphoma segmentation in PET images based on cellular automata - Paul Desbordes; Caroline Petitjean; Su Ruan (4th International Conference on Image Processing Theory, Tools and Applications, IPTA 2014, Paris, France, October 14-17, 2014, 2014)

Joint segmentation of right and left cardiac ventricles using multi-label graph cut - Damien Grosgeorge; Caroline Petitjean; Su Ruan (IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29 - May 2, 2014, Beijing, Chin, Beijing, China, 2014)

Prostate cancer segmentation from multiparametric MRI based on fuzzy Bayesian model - Yu Guo; Su Ruan; Paul Walker; Yuanming Feng (IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29 - May 2, 2014, Beijing, Chin, Beijing, China, 2014)

Automatic lung tumor segmentation on PET images based on random walks and tumor growth model - Hongmei Mi; Caroline Petitjean; Bernard Dubray; Pierre Vera; Su Ruan (IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29 - May 2, 2014, Beijing, Chin, Beijing, China, 2014)

Statistical Models of Shape and Spatial Relation-application to Hippocampus Segmentation - Saïd Ettaïeb; Kamel Hamrouni; Su Ruan (VISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications, Volume 1, Lisbon, Portugal, 5-8 January, 2014, 2014)

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

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

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

Predicting lung tumor evolution during radiotherapy from PET images using a patient specific model - Hongmei Mi; Caroline Petitjean; Su Ruan; Pierre Vera; Bernard Dubray (10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013, 7-11 April, 2013, San Francisco, CA, USA, Proceedings, 2013)

Signal Separation with A Priori Knowledge Using Sparse Representation - Yu Guo; Su Ruan (Advances in Heuristic Signal Processing and Applications, 2013)

Using Belief Function Theory to Deal with Uncertainties and Imprecisions in Image Processing - Benoît Lelandais; Isabelle Gardin; Laurent Mouchard; Pierre Vera; Su Ruan (Belief Functions: Theory and Applications - Proceedings of the 2nd International Conference on Belief Functions, Compiègne, France, 9-11 May 2012, 2012)

Analyzing the intrinsic relations between the diffusion and fluid deformable registration methods - Xiangbo Lin; Su Ruan (5th International Conference on BioMedical Engineering and Informatics, BMEI 2012, Chongqing, China, October 16-18, 2012, 2012)

3D random walk based segmentation for lung tumor delineation in PET imaging - D. P. Onoma; Su Ruan; Isabelle Gardin; G. A. Monnehan; Romain Modzelewski; Pierre Vera (9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012, May 2-5, 2012, Barcelona, Spain, Proceedings, 2012)

Segmentation of Biological Target Volumes on Multi-tracer PET Images Based on Information Fusion for Achieving Dose Painting in Radiotherapy - Benoît Lelandais; Isabelle Gardin; Laurent Mouchard; Pierre Vera; Su Ruan (Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012 - 15th International Conference, Nice, France, October 1-5, 2012, Proceedings, Part I, 2012)

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

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

Image fusion for following-up brain tumor evolution - Su Ruan; Nan Zhang; Qingmin Liao; Yuemin Zhu (Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2011, March 30 - April 2, 2011, Chicago, Illinois, USA, 2011)

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

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

A Sparse Representation Method for Magnetic Resonance Spectroscopy Quantification - Yu Guo; Su Ruan; Jérôme Landré; Jean-Marc Constans (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 - Xiaobing Li; Tianshuang Qiu; Stéphane Lebonvallet; Su Ruan (Second International Conference on Digital Image Processing, ICDIP 2010, Singapore, Singapore, February 26-28, 2010, 2010)

Fusion and classification of multi-source images by SVM with selected features in a kernel space - Su Ruan; Nan Zhang; Stéphane Lebonvallet; Qingmin Liao; Yue Min Zhu (2nd International Conference on Image Processing Theory Tools and Applications, IPTA 2010, 7-10 July, 2010, Paris, France, 2010)

Graph cut segmentation technique for MRI brain tumor extraction - Victor Chen; Su Ruan (2nd International Conference on Image Processing Theory Tools and Applications, IPTA 2010, 7-10 July, 2010, Paris, France, 2010)

Binary pattern matching from a local dissimilarity measure - Frédéric Morain-Nicolier; Jérôme Landré; Su Ruan (2nd International Conference on Image Processing Theory Tools and Applications, IPTA 2010, 7-10 July, 2010, Paris, France, 2010)

Spectrum separation of Magnetic Resonance Spectroscopy based on sparse representation - Yu Guo; Su Ruan; Gilles Millon; Jean-Marc Constans (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, 19-24 April 2009, Taipei, Taiwan, 2009)

Ornamental Letters Image Classification Using Local Dissimilarity Maps - Jérôme Landré; Frédéric Morain-Nicolier; Su Ruan (10th International Conference on Document Analysis and Recognition, ICDAR 2009, Barcelona, Spain, 26-29 July 2009, 2009)

Multi-kernel SVM based classification for brain tumor segmentation of MRI multi-sequence - Nan Zhang; Su Ruan; Stéphane Lebonvallet; Qingmin Liao; Yuemin Zhu (Proceedings of the International Conference on Image Processing, ICIP 2009, 7-10 November 2009, Cairo, Egypt, 2009)

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

Segmentation of Brain Internal Structures Automatically Using Non-rigid Registration with Simultaneous Intensity and Geometric Match - Xiangbo Lin; Tianshuang Qiu; Su Ruan; Frédéric Morain-Nicolier (Eighth International Conference on Intelligent Systems Design and Applications, ISDA 2008, 26-28 November 2008, Kaohsiung, Taiwan, 3 Volumes, 2008)

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

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

Tumor Segmentation from a Multispectral MRI Images by Using Support Vector Machine Classification - Su Ruan; Stéphane Lebonvallet; Abderrahim Merabet; Jean-Marc Constans (Proceedings of the 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Washington, DC, USA, April 12-16, 2007, 2007)

MRI segmentation using multifractal analysis and MRF models - Su Ruan; Jonathan Bailleul (VISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 8-11, 2007 - Volume Special Sessions, 2007)

Automated tumor segmentation using level set methods - Stéphane Lebonvallet; Sonia Khatchadourian; Su Ruan (VISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 8-11, 2007 - Volume Special Sessions, 2007)

A fast binary-image comparison method with local-dissimilarity quantification - Étienne Baudrier; Gilles Millon; Frédéric Nicolier; Su Ruan (18th International Conference on Pattern Recognition (ICPR 2006), 20-24 August 2006, Hong Kong, China, 2006)

A Smart Identification Card System Using Facial Biometric: From Architecture to Application - Kun Peng; Liming Chen; Su Ruan (Ubiquitous Intelligence and Computing, Third International Conference, UIC 2006, Wuhan, China, September 3-6, 2006, Proceedings, 2006)

A novel scheme of face verification using active appearance models - Kun Peng; Liming Chen; Su Ruan (Advanced Video and Signal Based Surveillance, 2005 IEEE International Conference on Video and Signal Based Surveillance (AVSS'05), 15-16 September 2005, Como, Italy, 2005)

Histogram-Based Generation Method of Membership Function for Extracting Features of Brain Tissues on MRI Images - Weibei Dou; Yuan Ren; Yanping Chen; Su Ruan; Daniel Bloyet; Jean-Marc Constans (Fuzzy Systems and Knowledge Discovery, Second International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I, 2005)

A Robust and Efficient Algorithm for Eye Detection on Gray Intensity Face - Kun Peng; Liming Chen; Su Ruan; Georgy Kukharev (Pattern Recognition and Image Analysis, Third International Conference on Advances in Pattern Recognition, ICAPR 2005, Bath, UK, August 22-25, 2005, Proceedings, Part II, 2005)

A new similarity measure using hausdorff distance map - Étienne Baudrier; Gilles Millon; Frédéric Nicolier; Su Ruan (Proceedings of the 2004 International Conference on Image Processing, ICIP 2004, Singapore, October 24-27, 2004, 2004)

Segmentation of anatomical structures from 3D brain MRI using automatically-built statistical shape models - Jonathan Bailleul; Su Ruan; Daniel Bloyet; Barbara Romaniuk (Proceedings of the 2004 International Conference on Image Processing, ICIP 2004, Singapore, October 24-27, 2004, 2004)

3d medical image segmentation approach based on multi-label front propagation - Hua Li; Abderrahim Elmoataz; Jalal Fadili; Su Ruan; Barbara Romaniuk (Proceedings of the 2004 International Conference on Image Processing, ICIP 2004, Singapore, October 24-27, 2004, 2004)

A Multi-Label Front Propagation Approach for Object Segmentation - Hua Li; Abderrahim Elmoataz; Mohamed-Jalal Fadili; Su Ruan (17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, August 23-26, 2004, 2004)

Segmentation based on information fusion applied to brain tissue on MRI - Weibei Dou; Su Ruan; Daniel Bloyet; Jean-Marc Constans; Yanping Chen (Image Processing: Algorithms and Systems III, San Jose, California, USA, January 18, 2004, 2004)

Dual Front Evolution Model and Its Application in Medical Imaging - Hua Li; Abderrahim Elmoataz; Mohamed-Jalal Fadili; Su Ruan (Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004, 7th International Conference Saint-Malo, France, September 26-29, 2004, Proceedings, Part I, 2004)

Possibilistic-clustering-based MR brain image segmentation with accurate initialization - Qingmin Liao; Yingying Deng; Weibei Dou; Su Ruan; Daniel Bloyet (Visual Communications and Image Processing 2004, VCIP 2004, San Jose, California, USA, 18-22 January 2004, 2004)

Automatic atlas-based building of point distribution model for segmentation of anatomical structures from brain MRI - Jonathan Bailleul; Su Ruan; Daniel Bloyet (Seventh International Symposium on Signal Processing and Its Applications, ISSPA 2003, July 1-4, 2003, Paris, France, Proceedings, Volume 2, 2003)

Knowledge based fuzzy information fusion applied to classification of abnormal brain tissues from MRI - Weibei Dou; Su Ruan; Qingmin Liao; Daniel Bloyet; Jean-Marc Constans (Seventh International Symposium on Signal Processing and Its Applications, ISSPA 2003, July 1-4, 2003, Paris, France, Proceedings, Volume 1, 2003)

Fuzzy Information Fusion Scheme Used to Segment Brain Tumor from MR Images - Weibei Dou; Su Ruan; Qingmin Liao; Daniel Bloyet; Jean-Marc Constans; Yanping Chen (Fuzzy Logic and Applications, 5th International Workshop, WILF 2003, Naples, Italy, October 9-11, 2003, Revised Selected Papers, 2003)

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

Cerebral magnetic resonance image segmentation using fuzzy Markov Random Fields - Su Ruan; Daniel Bloyet; Marinette Revenu; Weibei Dou; Qingmin Liao (Proceedings of the 2002 IEEE International Symposium on Biomedical Imaging, Ritz-Carlton Hotel, Washington, DC, USA, 7-10 June 2002, 2002)

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

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

Segmentation of magnetic resonance images using fuzzy Markov random fields - Su Ruan; Bruno Moretti; Jalal Fadili; Daniel Bloyet (Proceedings of the 2001 International Conference on Image Processing, ICIP 2001, Thessaloniki, Greece, October 7-10, 2001, 2001)

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

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

Fuzzy Modeling of Knowledge for MRI Brain Structure Segmentation - Jing-Hao Xue; Su Ruan; Bruno Moretti; Marinette Revenu; Daniel Bloyet; Wilfried Philips (Proceedings of the 2000 International Conference on Image Processing, ICIP 2000, Vancouver, BC, Canada, September 10-13, 2000, 2000)

Unsupervised Segmentation of Three-Dimensional Brain Images - Su Ruan; Mohamed-Jalal Fadili; Daniel Bloyet; Jing-Hao Xue (15th International Conference on Pattern Recognition, ICPR'00, Barcelona, Spain, September 3-8, 2000, 2000)

Detection of Brain Activation from MRI Data by Likelihood-Ratio Test - Su Ruan; Cyril Jaggi; Jean-Marc Constans; Daniel Bloyet (Computer Vision, Virtual Reality and Robotics in Medicine, First International Conference, CVRMed'95, Nice, France, April 3-6, 1995, Proceedings, 1995)

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