Pierre Vera
According to our database1,
Pierre Vera
authored at least 51 papers
between 2010 and 2024.
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Bibliography
2024
Efficient brain tumor segmentation using Swin transformer and enhanced local self-attention.
Int. J. Comput. Assist. Radiol. Surg., February, 2024
2023
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks.
CoRR, 2023
Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy.
Proceedings of the Twelfth International Conference on Image Processing Theory, 2023
2022
Missing Data Imputation via Conditional Generator and Correlation Learning for Multimodal Brain Tumor Segmentation.
Pattern Recognit. Lett., 2022
Pattern Recognit., 2022
Weakly Supervised Tumor Detection in PET Using Class Response for Treatment Outcome Prediction.
J. Imaging, 2022
A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction.
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.
Entropy, 2022
Comput. Biol. Medicine, 2022
Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT.
Proceedings of the Head and Neck Tumor Segmentation and Outcome Prediction, 2022
2021
Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities.
IEEE Trans. Image Process., 2021
Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities.
Neurocomputing, 2021
A Dual Supervision Guided Attentional Network for Multimodal MR Brain Tumor Segmentation.
Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis, 2021
2020
UMI-VarCal: a new UMI-based variant caller that efficiently improves low-frequency variant detection in paired-end sequencing NGS libraries.
Bioinform., 2020
Brain Tumor Segmentation with Missing Modalities via Latent Multi-source Correlation Representation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
3D Medical Multi-modal Segmentation Network Guided by Multi-source Correlation Constraint.
Proceedings of the 25th International Conference on Pattern Recognition, 2020
RADIOGAN: Deep Convolutional Conditional Generative Adversarial Network to Generate PET Images.
Proceedings of the ICBRA 2020: 7th International Conference on Bioinformatics Research and Applications, 2020
2019
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions.
IEEE Trans. Image Process., 2019
Adaptive kernelized evidential clustering for automatic 3D tumor segmentation in FDG-PET images.
Multim. Syst., 2019
Anthropometer3D: Automatic Multi-Slice Segmentation Software for the Measurement of Anthropometric Parameters from CT of PET/CT.
J. Digit. Imaging, 2019
Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy.
Int. J. Comput. Assist. Radiol. Surg., 2019
Gaussian-based Spatial Hybrid Distances for Detection and Segmentation of Lymphoid Lesions in 3D PET Images.
Proceedings of the 12th International Congress on Image and Signal Processing, 2019
A Background-based Data Enhancement Method for Lymphoma Segmentation in 3D PET Images.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
A Prior Knowledge Intergrated Scheme for Detection and Segmentation of Lymphomas in 3D PET Images based on DBSCAN and GAs.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
2018
Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images.
IEEE Trans. Biomed. Eng., 2018
Semi-automatic lymphoma detection and segmentation using fully conditional random fields.
Comput. Medical Imaging Graph., 2018
Unsupervised co-segmentation of tumor in PET-CT images using belief functions based fusion.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2017
Feature selection for outcome prediction in oesophageal cancer using genetic algorithm and random forest classifier.
Comput. Medical Imaging Graph., 2017
Proceedings of the Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment, 2017
Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017
2016
Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction.
Medical Image Anal., 2016
Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
2015
Joint tumor growth prediction and tumor segmentation on therapeutic follow-up PET images.
Medical Image Anal., 2015
Monte-Carlo simulations of clinically realistic respiratory gated <sup>18</sup>F-FDG PET: Application to lesion detectability and volume measurements.
Comput. Methods Programs Biomed., 2015
Artif. Intell. Medicine, 2015
Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015
2014
Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET.
IEEE Trans. Medical Imaging, 2014
Dealing with uncertainty and imprecision in image segmentation using belief function theory.
Int. J. Approx. Reason., 2014
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.
Comput. Medical Imaging Graph., 2014
Automatic lung tumor segmentation on PET images based on random walks and tumor growth model.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014
2013
Predicting lung tumor evolution during radiotherapy from PET images using a patient specific model.
Proceedings of the 10th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2013
2012
Segmentation of Biological Target Volumes on Multi-tracer PET Images Based on Information Fusion for Achieving Dose Painting in Radiotherapy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012
Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012
Using Belief Function Theory to Deal with Uncertainties and Imprecisions in Image Processing.
Proceedings of the Belief Functions: Theory and Applications, 2012
2010
Brain perfusion heterogeneity measurement based on Random Walk algorithm: Choice and influence of inner parameters.
Comput. Medical Imaging Graph., 2010