Su Ruan

ORCID

Publication Activity (10 Years)

Years Active: 1994-2024
Publications (10 Years): 112

Top Venues

CoRR

ISBI

Medical Image Anal.

Comput. Medical Imaging Graph.

Publications

Zexin Ji, Beiji Zou, Xiaoyan Kui, Pierre Vera, Su Ruan
Deform-Mamba Network for MRI Super-Resolution. CoRR (2024)
Fethi Ghazouani, Pierre Vera, Su Ruan
Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention. Int. J. Comput. Assist. Radiol. Surg. 19 (2) (2024)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes. Neurocomputing 606 (2024)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce Regimes. CoRR (2024)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes. CoRR (2024)
Zexin Ji, Beiji Zou, Xiaoyan Kui, Pierre Vera, Su Ruan
Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution. CoRR (2024)
Ling Huang, Su Ruan, Yucheng Xing, Mengling Feng
A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods. Medical Image Anal. 97 (2024)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks. CoRR (2023)
Tongxue Zhou, Alexandra Noeuveglise, Romain Modzelewski, Fethi Ghazouani, Sébastien Thureau, Maxime Fontanilles, Su Ruan
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning. CoRR (2023)
Tongxue Zhou, Alexandra Noeuveglise, Romain Modzelewski, Fethi Ghazouani, Sébastien Thureau, Maxime Fontanilles, Su Ruan
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning. Comput. Medical Imaging Graph. 106 (2023)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Hua Li, Pierre Vera, Pierre Decazes, Su Ruan
Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy. IPTA (2023)
Lixin Zhang, Yulun Sun, Pierre Decazes, Su Ruan, Yu Guo, Hui Yu
One-shot Learning for DLBCL Segmentation in Whole Body PET/CT Images. ISBI (2023)
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation. CoRR (2023)
Ling Huang, Su Ruan, Thierry Denoeux
Application of belief functions to medical image segmentation: A review. Inf. Fusion 91 (2023)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. J. Imaging 9 (4) (2023)
Ling Huang, Su Ruan, Yucheng Xing, Mengling Feng
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods. CoRR (2023)
Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Su Ruan
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review. CoRR (2023)
Tongxue Zhou, Su Ruan, Haigen Hu
A literature survey of MR-based brain tumor segmentation with missing modalities. Comput. Medical Imaging Graph. 104 (2023)
Ling Huang, Su Ruan, Thierry Denoeux
Semi-supervised multiple evidence fusion for brain tumor segmentation. Neurocomputing 535 (2023)
Zhengshan Huang, Yu Guo, Ning Zhang, Xian Huang, Pierre Decazes, Stephanie Becker, Su Ruan
Multi-scale feature similarity-based weakly supervised lymphoma segmentation in PET/CT images. Comput. Biol. Medicine 151 (Part) (2022)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 24 (4) (2022)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
A Quantitative Comparison between Shannon and Tsallis Havrda Charvat Entropies Applied to Cancer Outcome Prediction. CoRR (2022)
Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan
Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images. CoRR (2022)
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux
Lymphoma segmentation from 3D PET-CT images using a deep evidential network. CoRR (2022)
Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan
Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction. J. Imaging 8 (5) (2022)
Ling Huang, Su Ruan
Application of belief functions to medical image segmentation: A review. CoRR (2022)
Haigen Hu, Leizhao Shen, Qiu Guan, Xiaoxin Li, Qianwei Zhou, Su Ruan
Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images. Pattern Recognit. 124 (2022)
Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan
Multi-task multi-scale learning for outcome prediction in 3D PET images. Comput. Biol. Medicine 151 (Part) (2022)
Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan
Evidence fusion with contextual discounting for multi-modality medical image segmentation. CoRR (2022)
Zong Fan, Xiaohui Zhang, Jacob A. Gasienica, Jennifer Potts, Su Ruan, Wade Thorstad, Hiram Gay, Xiaowei Wang, Hua Li
A novel adversarial learning strategy for medical image classification. CoRR (2022)
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, Hesham Elhalawani, Clifton D. Fuller, Mario Jreige, Yomna Khamis, Agustina La Greca Saint-Esteven, Abdallah Mohamed, Mohamed Naser, John O. Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallières, Pierre Vera, Dimitris Visvikis, Kareem Wahid, Habib Zaidi, Mathieu Hatt, Adrien Depeursinge
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT. HECKTOR@MICCAI (2022)
Tongxue Zhou, Pierre Vera, Stéphane Canu, Su Ruan
Missing Data Imputation via Conditional Generator and Correlation Learning for Multimodal Brain Tumor Segmentation. Pattern Recognit. Lett. 158 (2022)
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux
Lymphoma segmentation from 3D PET-CT images using a deep evidential network. Int. J. Approx. Reason. 149 (2022)
Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan
Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. MICCAI (5) (2022)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Alexandre Huat, Sébastien Thureau, David Pasquier, Isabelle Gardin, Romain Modzelewski, David Gibon, Juliette Thariat, Vincent Grégoire, Pierre Vera, Su Ruan
Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. Entropy 2022, 24, 436. Entropy 24 (5) (2022)
Tongxue Zhou, Alexandra Noeuveglise, Fethi Ghazouani, Romain Modzelewski, Sébastien Thureau, Maxime Fontanilles, Su Ruan
Prediction of Brain Tumor Recurrence Location Based on Kullback-Leibler Divergence and Nonlinear Correlation Learning. ICPR (2022)
Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu
A Tri-Attention fusion guided multi-modal segmentation network. Pattern Recognit. 124 (2022)
Haigen Hu, Leizhao Shen, Qiu Guan, Xiaoxin Li, Qianwei Zhou, Su Ruan
Deep Co-supervision and Attention Fusion Strategy for Automatic COVID-19 Lung Infection Segmentation on CT Images. CoRR (2021)
Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan
Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation. MLMI@MICCAI (2021)
Zong Fan, Shenghua He, Su Ruan, Xiaowei Wang, Hua Li
Deep learning-based multi-class COVID-19 classification with x-ray images. Medical Imaging: Image-Guided Procedures (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation. MICAD (2021)
Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim
AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics. CoRR (2021)
Ling Huang, Su Ruan, Thierry Denoeux
Covid-19 classification with deep neural network and belief functions. CoRR (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. CoRR (2021)
Shenghua He, Chunfeng Lian, Wade Thorstad, Hiram Gay, Yujie Zhao, Su Ruan, Xiaowei Wang, Hua Li
A novel systematic approach for cancer treatment prognosis and its applications in oropharyngeal cancer with microRNA biomarkers. Bioinform. 37 (19) (2021)
Ling Huang, Su Ruan, Thierry Denoeux
Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation. ISBI (2021)
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux
Evidential Segmentation of 3D PET/CT Images. BELIEF (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities. IEEE Trans. Image Process. 30 (2021)
Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu
A Tri-attention Fusion Guided Multi-modal Segmentation Network. CoRR (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities. Neurocomputing 466 (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities. CoRR (2021)
Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux
Evidential segmentation of 3D PET/CT images. CoRR (2021)
Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan
Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation. CoRR (2021)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Sébastien Bougleux, Mathieu Salaün, Su Ruan
Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy. CoRR (2021)
Tongxue Zhou, Stéphane Canu, Su Ruan
Automatic COVID-19 CT segmentation using U-Net integrated spatial and channel attention mechanism. Int. J. Imaging Syst. Technol. 31 (1) (2021)
Ling Huang, Su Ruan, Thierry Denoeux
Belief function-based semi-supervised learning for brain tumor segmentation. CoRR (2021)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Feature-enhanced Generation and Multi-modality Fusion based Deep Neural Network for Brain Tumor Segmentation with Missing MR Modalities. CoRR (2021)
Ling Huang, Su Ruan, Thierry Denoeux
Covid-19 Classification with Deep Neural Network and Belief Functions. BIBE (2021)
Dong Nie, Roger Trullo, Jun Lian, Li Wang, Caroline Petitjean, Su Ruan, Qian Wang, Dinggang Shen
Corrections to "Medical Image Synthesis With Deep Convolutional Adversarial Networks". IEEE Trans. Biomed. Eng. 67 (9) (2020)
Haigen Hu, Leizhao Shen, Tongxue Zhou, Pierre Decazes, Pierre Vera, Su Ruan
Lymphoma Segmentation in PET Images Based on Multi-view and Conv3D Fusion Strategy. ISBI (2020)
Tongxue Zhou, Stéphane Canu, Su Ruan
Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation. Comput. Medical Imaging Graph. 86 (2020)
Tongxue Zhou, Su Ruan, Stéphane Canu
A review: Deep learning for medical image segmentation using multi-modality fusion. CoRR (2020)
Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan
Weakly Supervised PET Tumor Detection Using Class Response. CoRR (2020)
Amine Amyar, Romain Modzelewski, Hua Li, Su Ruan
Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation. Comput. Biol. Medicine 126 (2020)
Thibaud Brochet, Jérôme Lapuyade-Lahorgue, Sébastien Bougleux, Mathieu Salaün, Su Ruan
Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy. IPTA (2020)
Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan
Incoherent dictionary learning via mixed-integer programming and hybrid augmented Lagrangian. Digit. Signal Process. 101 (2020)
Amine Amyar, Su Ruan, Pierre Vera, Pierre Decazes, Romain Modzelewski
RADIOGAN: Deep Convolutional Conditional Generative adversarial Network To Generate PET Images. CoRR (2020)
Tongxue Zhou, Stéphane Canu, Su Ruan
An automatic COVID-19 CT segmentation network using spatial and channel attention mechanism. CoRR (2020)
Yu Guo, Pierre Decazes, Stéphanie Becker, Hua Li, Su Ruan
Deep Disentangled Representation Learning of Pet Images for Lymphoma Outcome Prediction. ISBI (2020)
Zoé Lambert, Caroline Petitjean, Bernard Dubray, Su Ruan
SegTHOR: Segmentation of Thoracic Organs at Risk in CT images. IPTA (2020)
Amine Amyar, Su Ruan, Pierre Vera, Pierre Decazes, Romain Modzelewski
RADIOGAN: Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images. ICBRA (2020)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Brain tumor segmentation with missing modalities via latent multi-source correlation representation. CoRR (2020)
Tongxue Zhou, Su Ruan, Yu Guo, Stéphane Canu
A Multi-Modality Fusion Network Based on Attention Mechanism for Brain Tumor Segmentation. ISBI (2020)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. ICPR (2020)
Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan
Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation. MICCAI (4) (2020)
Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions. IEEE Trans. Image Process. 28 (2) (2019)
Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan
Mixed Integer Programming For Sparse Coding: Application to Image Denoising. IEEE Trans. Computational Imaging 5 (3) (2019)
Haigen Hu, Chao Du, Pierre Decazes, Pierre Vera, Su Ruan
A Prior Knowledge Intergrated Scheme for Detection and Segmentation of Lymphomas in 3D PET Images based on DBSCAN and GAs. BIBM (2019)
Tongxue Zhou, Su Ruan, Haigen Hu, Stéphane Canu
Deep Learning Model Integrating Dilated Convolution and Deep Supervision for Brain Tumor Segmentation in Multi-parametric MRI. MLMI@MICCAI (2019)
Fan Wang, Chunfeng Lian, Pierre Vera, Su Ruan
Adaptive kernelized evidential clustering for automatic 3D tumor segmentation in FDG-PET images. Multim. Syst. 25 (2) (2019)
Haigen Hu, Pierre Decazes, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan
Gaussian-based Spatial Hybrid Distances for Detection and Segmentation of Lymphoid Lesions in 3D PET Images. CISP-BMEI (2019)
Zoé Lambert, Caroline Petitjean, Bernard Dubray, Su Ruan
SegTHOR: Segmentation of Thoracic Organs at Risk in CT images. CoRR (2019)
Tongxue Zhou, Su Ruan, Stéphane Canu
A review: Deep learning for medical image segmentation using multi-modality fusion. Array (2019)
Haigen Hu, Chao Du, Qiu Guan, Qianwei Zhou, Pierre Vera, Su Ruan
A Background-based Data Enhancement Method for Lymphoma Segmentation in 3D PET Images. BIBM (2019)
Haigen Hu, Pierre Decazes, Pierre Vera, Hua Li, Su Ruan
Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy. Int. J. Comput. Assist. Radiol. Surg. 14 (10) (2019)
Chunfeng Lian, Hua Li, Pierre Vera, Su Ruan
Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion. ISBI (2018)
Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan
K-SVD with a Real ℓ0 Optimization: Application to Image Denoising. MLSP (2018)
Jian Wu, Su Ruan, Chunfeng Lian, Sasa Mutic, Mark A. Anastasio, Hua Li
Active learning with noise modeling for medical image annotation. ISBI (2018)
Dong Nie, Roger Trullo, Jun Lian, Li Wang, Caroline Petitjean, Su Ruan, Qian Wang, Dinggang Shen
Medical Image Synthesis with Deep Convolutional Adversarial Networks. IEEE Trans. Biomed. Eng. 65 (12) (2018)
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, Hua Li
Heart motion tracking on cine MRI based on a deep Boltzmann machine-driven level set method. ISBI (2018)
Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera
Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images. IEEE Trans. Biomed. Eng. 65 (1) (2018)
Naouel Boughattas, Maxime Berar, Kamel Hamrouni, Su Ruan
Feature selection and classification using multiple kernel learning for brain tumor segmentation. ATSIP (2018)
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, Hua Li
A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images. Medical Image Anal. 47 (2018)
Jierui Zha, Pierre Decazes, Jérôme Lapuyade, Abderrahim Elmoataz, Su Ruan
3D lymphoma detection in PET-CT images with supervoxel and CRFs. IPTA (2018)
Yuntao Yu, Pierre Decazes, Jérôme Lapuyade-Lahorgue, Isabelle Gardin, Pierre Vera, Su Ruan
Semi-automatic lymphoma detection and segmentation using fully conditional random fields. Comput. Medical Imaging Graph. 70 (2018)
Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera
Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric. ISBI (2017)
Yuntao Yu, Pierre Decazes, Isabelle Gardin, Pierre Vera, Su Ruan
3D Lymphoma Segmentation in PET/CT Images Based on Fully Connected CRFs. CMMI/RAMBO/SWITCH@MICCAI (2017)
Roger Trullo, Caroline Petitjean, Dong Nie, Dinggang Shen, Su Ruan
Fully automated esophagus segmentation with a hierarchical deep learning approach. ICSIPA (2017)
Paul Desbordes, Su Ruan, Romain Modzelewski, Vauclin Sébastien, Pierre Vera, Isabelle Gardin
Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier. Comput. Medical Imaging Graph. 60 (2017)
Roger Trullo, Caroline Petitjean, Su Ruan, Bernard Dubray, Dong Nie, Dinggang Shen
Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields. ISBI (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Su Ruan