Carole Lartizien
Orcid: 0000-0001-7594-4231
According to our database1,
Carole Lartizien
authored at least 46 papers
between 2004 and 2024.
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Bibliography
2024
Medical Image Anal., 2024
Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
2023
Anomaly detection in image or latent space of patch-based auto-encoders for industrial image analysis.
CoRR, 2023
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities.
Proceedings of the Medical Imaging with Deep Learning, 2023
Whole brain radiomics for clustered federated personalization in brain tumor segmentation.
Proceedings of the Medical Imaging with Deep Learning, 2023
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Brain Subtle Anomaly Detection Based on Auto-Encoders Latent Space Analysis: Application To De Novo Parkinson Patients.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans.
Medical Image Anal., 2022
Learning to segment prostate cancer by aggressiveness from scribbles in bi-parametric MRI.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Perfusion Imaging in Deep Prostate Cancer Detection from MP-MRI: Can We Take Advantage of it?
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
2021
GAN-Based Synthetic FDG PET Images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection Models.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2021
Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients.
Proceedings of the Machine Learning in Clinical Neuroimaging - 4th International Workshop, 2021
2020
Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening.
Medical Image Anal., 2020
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography.
CoRR, 2020
Priority U-Net: Detection of Punctuate White Matter Lesions in Preterm Neonate in 3D Cranial Ultrasonography.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Prostate Cancer Semantic Segmentation by Gleason Score Group in bi-parametric MRI with Self Attention Model on the Peripheral Zone.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography.
IEEE Trans. Medical Imaging, 2019
Exploiting GPUs on distributed infrastructures for medical imaging applications with VIP and DIRAC.
Proceedings of the 42nd International Convention on Information and Communication Technology, 2019
2018
Feature extraction with regularized siamese networks for outlier detection: application to lesion screening in medical imaging.
CoRR, 2018
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018
Unsupervised Feature Learning for Outlier Detection with Stacked Convolutional Autoencoders, Siamese Networks and Wasserstein Autoencoders: Application to Epilepsy Detection.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018
2017
Neurocomputing, 2017
2016
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016
2015
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015
Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR Imaging Databases.
Proceedings of the Machine Learning Meets Medical Imaging - First International Workshop, 2015
Analyse psychophysique et apprentissage statistique pour l'aide au diagnostic en imagerie du cancer.
, 2015
2014
Computer-Aided Staging of Lymphoma Patients With FDG PET/CT Imaging Based on Textural Information.
IEEE J. Biomed. Health Informatics, 2014
Kernel-Based Learning From Both Qualitative and Quantitative Labels: Application to Prostate Cancer Diagnosis Based on Multiparametric MR Imaging.
IEEE Trans. Image Process., 2014
OntoVIP: An ontology for the annotation of object models used for medical image simulation.
J. Biomed. Informatics, 2014
SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014
Computer-aided diagnostic system for prostate cancer detection and characterization combining learned dictionaries and supervised classification.
Proceedings of the 2014 IEEE International Conference on Image Processing, 2014
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014
2013
IEEE Trans. Medical Imaging, 2013
Computer Aided Diagnosis of Intractable Epilepsy with MRI Imaging Based on Textural Information.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
2012
Computer aided staging of lymphoma patients with FDG PET/CT imaging based on textural information.
Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012
Multi-modality image simulation with the Virtual Imaging Platform: Illustration on cardiac echography and MRI.
Proceedings of the 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2012
2011
Computer-aided tumor detection stemmed from the fuzzification of the Dempster-Shafer theory.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011
Computer-aided diagnosis for prostate cancer detection in the peripheral zone via multisequence MRI.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011
Multi-modality medical image simulation of biological models with the Virtual Imaging Platform (VIP).
Proceedings of the 24th IEEE International Symposium on Computer-Based Medical Systems, 2011
Sharing object models for multi-modality medical image simulation: A semantic approach.
Proceedings of the 24th IEEE International Symposium on Computer-Based Medical Systems, 2011
2010
IEEE Trans. Medical Imaging, 2010
2009
Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body <sup>18</sup>hboxF-FDG Distributions for Oncology Applications.
Proc. IEEE, 2009
2004
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2004