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2020 – today
- 2024
[j27]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): 273-281 (2024)- [j26]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
Discriminative Hamiltonian variational autoencoder for accurate tumor segmentation in data-scarce regimes. Neurocomputing 606: 128360 (2024) - [c25]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. ISBI 2024: 1-5 - [c24]Zexin Ji, Beiji Zou, Xiaoyan Kui, Pierre Vera, Su Ruan:
Deform-Mamba Network for MRI Super-Resolution. MICCAI (7) 2024: 242-252 - [i15]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 abs/2406.05421 (2024) - [i14]Aghiles Kebaili, Jérôme Lapuyade-Lahorgue, Pierre Vera, Su Ruan:
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes. CoRR abs/2406.11659 (2024) - [i13]Zexin Ji, Beiji Zou, Xiaoyan Kui, Pierre Vera, Su Ruan:
Deform-Mamba Network for MRI Super-Resolution. CoRR abs/2407.05969 (2024) - [i12]Zexin Ji, Beiji Zou, Xiaoyan Kui, Pierre Vera, Su Ruan:
Self-Prior Guided Mamba-UNet Networks for Medical Image Super-Resolution. CoRR abs/2407.05993 (2024) - 2023
- [c23]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: 1-5 - [i11]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 abs/2311.10472 (2023) - 2022
- [j25]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): 106208 (2022) - [j24]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): 436 (2022) - [j23]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): 685 (2022) - [j22]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): 130 (2022) - [j21]Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu:
A Tri-Attention fusion guided multi-modal segmentation network. Pattern Recognit. 124: 108417 (2022) - [j20]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: 125-132 (2022) - [c22]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 Sherif Radwan Mohamed, Mohamed A. Naser, John O. Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallières, Pierre Vera, Dimitris Visvikis, Kareem A. 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: 1-30 - [c21]Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan:
Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. MICCAI (5) 2022: 401-411 - [i10]Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan:
Multi-Task Multi-Scale Learning For Outcome Prediction in 3D PET Images. CoRR abs/2203.00641 (2022) - [i9]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 abs/2203.11943 (2022) - [i8]Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan:
Evidence fusion with contextual discounting for multi-modality medical image segmentation. CoRR abs/2206.11739 (2022) - 2021
- [j19]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: 102-112 (2021) - [j18]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: 4263-4274 (2021) - [c20]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation. MICAD 2021: 3-11 - [i7]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. CoRR abs/2102.03111 (2021) - [i6]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
Latent Correlation Representation Learning for Brain Tumor Segmentation with Missing MRI Modalities. CoRR abs/2104.06231 (2021) - [i5]Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu:
A Tri-attention Fusion Guided Multi-modal Segmentation Network. CoRR abs/2111.01623 (2021) - [i4]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 abs/2111.04735 (2021) - 2020
- [j17]Vincent Sater, Pierre-Julien Viailly, Thierry Lecroq, Élise Prieur-Gaston, Élodie Bohers, Mathieu Viennot, Philippe Ruminy, Hélène Dauchel, Pierre Vera, Fabrice Jardin:
UMI-VarCal: a new UMI-based variant caller that efficiently improves low-frequency variant detection in paired-end sequencing NGS libraries. Bioinform. 36(9): 2718-2724 (2020) - [c19]Amine Amyar, Su Ruan, Pierre Vera, Pierre Decazes, Romain Modzelewski:
RADIOGAN: Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images. ICBRA 2020: 28-33 - [c18]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint. ICPR 2020: 10243-10250 - [c17]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: 1197-1200 - [c16]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation. MICCAI (4) 2020: 533-541 - [i3]Amine Amyar, Romain Modzelewski, Pierre Vera, Vincent Morard, Su Ruan:
Weakly Supervised PET Tumor Detection Using Class Response. CoRR abs/2003.08337 (2020) - [i2]Amine Amyar, Su Ruan, Pierre Vera, Pierre Decazes, Romain Modzelewski:
RADIOGAN: Deep Convolutional Conditional Generative adversarial Network To Generate PET Images. CoRR abs/2003.08663 (2020) - [i1]Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan:
Brain tumor segmentation with missing modalities via latent multi-source correlation representation. CoRR abs/2003.08870 (2020)
2010 – 2019
- 2019
- [j16]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): 1715-1724 (2019) - [j15]Pierre Decazes, David Tonnelet, Pierre Vera, Isabelle Gardin:
Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT. J. Digit. Imaging 32(2): 241-250 (2019) - [j14]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): 127-133 (2019) - [j13]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): 755-766 (2019) - [c15]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: 1194-1196 - [c14]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: 2413-2420 - [c13]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: 1-5 - 2018
- [j12]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: 1-7 (2018) - [j11]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): 21-30 (2018) - [c12]Chunfeng Lian, Hua Li, Pierre Vera, Su Ruan:
Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion. ISBI 2018: 220-223 - 2017
- [j10]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: 42-49 (2017) - [c11]Chunfeng Lian, Su Ruan, Thierry Denoeux, Yu Guo, Pierre Vera:
Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images. ICIP 2017: 4447-4451 - [c10]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: 1177-1180 - [c9]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: 3-12 - 2016
- [j9]Chunfeng Lian, Su Ruan, Thierry Denoeux, Fabrice Jardin, Pierre Vera:
Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. Medical Image Anal. 32: 257-268 (2016) - [c8]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images. MICCAI (2) 2016: 61-69 - 2015
- [j8]Hongmei Mi, Caroline Petitjean, Bernard Dubray, Pierre Vera, Su Ruan:
Robust feature selection to predict tumor treatment outcome. Artif. Intell. Medicine 64(3): 195-204 (2015) - [j7]S. Vauclin, Christian Michel, Irène Buvat, K. Doyeux, A. Edet-Sanson, Pierre Vera, Isabelle Gardin, S. Hapdey:
Monte-Carlo simulations of clinically realistic respiratory gated 18F-FDG PET: Application to lesion detectability and volume measurements. Comput. Methods Programs Biomed. 118(1): 84-93 (2015) - [j6]Hongmei Mi, Caroline Petitjean, Pierre Vera, Su Ruan:
Joint tumor growth prediction and tumor segmentation on therapeutic follow-up PET images. Medical Image Anal. 23(1): 84-91 (2015) - [c7]Chunfeng Lian, Su Ruan, Thierry Denoeux, Pierre Vera:
Outcome prediction in tumour therapy based on Dempster-Shafer theory. ISBI 2015: 63-66 - [c6]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy. MICCAI (3) 2015: 695-702 - 2014
- [j5]D. P. Onoma, Su Ruan, Sébastien Thureau, Lamyaa Nkhali, Romain Modzelewski, G. A. Monnehan, Pierre Vera, Isabelle Gardin:
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm. Comput. Medical Imaging Graph. 38(8): 753-763 (2014) - [j4]Benoît Lelandais, Isabelle Gardin, Laurent Mouchard, Pierre Vera, Su Ruan:
Dealing with uncertainty and imprecision in image segmentation using belief function theory. Int. J. Approx. Reason. 55(1): 376-387 (2014) - [j3]Benoît Lelandais, Su Ruan, Thierry Denoeux, Pierre Vera, Isabelle Gardin:
Fusion of multi-tracer PET images for dose painting. Medical Image Anal. 18(7): 1247-1259 (2014) - [j2]Hongmei Mi, Caroline Petitjean, Bernard Dubray, Pierre Vera, Su Ruan:
Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET. IEEE Trans. Medical Imaging 33(4): 995-1003 (2014) - [c5]Hongmei Mi, Caroline Petitjean, Bernard Dubray, Pierre Vera, Su Ruan:
Automatic lung tumor segmentation on PET images based on random walks and tumor growth model. ISBI 2014: 1385-1388 - 2013
- [c4]Hongmei Mi, Caroline Petitjean, Su Ruan, Pierre Vera, Bernard Dubray:
Predicting lung tumor evolution during radiotherapy from PET images using a patient specific model. ISBI 2013: 1404-1407 - 2012
- [c3]Benoît Lelandais, Isabelle Gardin, Laurent Mouchard, Pierre Vera, Su Ruan:
Using Belief Function Theory to Deal with Uncertainties and Imprecisions in Image Processing. Belief Functions 2012: 197-204 - [c2]D. P. Onoma, Su Ruan, Isabelle Gardin, G. A. Monnehan, Romain Modzelewski, Pierre Vera:
3D random walk based segmentation for lung tumor delineation in PET imaging. ISBI 2012: 1260-1263 - [c1]Benoît Lelandais, Isabelle Gardin, Laurent Mouchard, Pierre Vera, Su Ruan:
Segmentation of Biological Target Volumes on Multi-tracer PET Images Based on Information Fusion for Achieving Dose Painting in Radiotherapy. MICCAI (1) 2012: 545-552 - 2010
- [j1]Romain Modzelewski, Elise Janvresse, Thierry de la Rue, Pierre Vera:
Brain perfusion heterogeneity measurement based on Random Walk algorithm: Choice and influence of inner parameters. Comput. Medical Imaging Graph. 34(4): 289-297 (2010)
Coauthor Index
[j27] [j26] [c25] [c24] [i15] [i14] [i13] [i12] [c23] [i11] [j25] [j24] [j23] [j22] [j21] [j20] [c22] [c21] [i10] [i9] [i8] [j19] [j18] [c20] [i7] [i6] [i5] [i4] [c19] [c18] [c17] [c16] [i3] [i2] [i1] [j16] [j14] [j13] [c15] [c14] [c13] [j12] [j11] [c12] [j10] [c11] [c10] [c9] [j9] [c8] [j8] [j6] [c7] [c6] [j5] [j4] [j3] [j2] [c5] [c4] [c3] [c2] [c1]
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last updated on 2024-10-11 18:20 CEST by the dblp team
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