Effect of Scan Duration on Lesion Detectability in PET Oncology Imaging. - Phillip Cheng; Paul E. Kinahan; Jae-Seung Kim; Thomas K. Lewellen; Claude Comtat; Carole Lartizien (ISBI, 2004)

Incorporating Patient-Specific Variability in the Simulation of Realistic Whole-Body 18hboxF-FDG Distributions for Oncology Applications. - Amandine Le Maitre; William Paul Segars; Simon Marache; Anthonin Reilhac; Mathieu Hatt; Sandrine Tomeï; Carole Lartizien; Dimitris Visvikis (Proc. IEEE, 2009)

Comparison of Bootstrap Resampling Methods for 3-D PET Imaging. - Carole Lartizien; Jean-Baptiste Aubin; Irène Buvat (IEEE Trans. Medical Imaging, 2010)

Sharing object models for multi-modality medical image simulation: A semantic approach. - Germain Forestier; Adrien Marion; Hugues Benoit-Cattin; Patrick Clarysse; Denis Friboulet; Tristan Glatard; Patrick Hugonnard; Carole Lartizien; Hervé Liebgott; Joachim Tabary; Bernard Gibaud (CBMS, 2011)

Multi-modality medical image simulation of biological models with the Virtual Imaging Platform (VIP). - Adrien Marion; Germain Forestier; Hugues Benoit-Cattin; Sorina Camarasu-Pop; Patrick Clarysse; Rafael Ferreira da Silva; Bernard Gibaud; Tristan Glatard; Patrick Hugonnard; Carole Lartizien; Hervé Liebgott; Svenja Specovius; et al. (CBMS, 2011)

Computer-aided diagnosis for prostate cancer detection in the peripheral zone via multisequence MRI. - Emilie Niaf; Olivier Rouvière; Carole Lartizien (Computer-Aided Diagnosis, 2011)

Computer-aided tumor detection stemmed from the fuzzification of the Dempster-Shafer theory. - Obioma Udobata; Chantal Revol-Muller; Carole Lartizien (Computer-Aided Diagnosis, 2011)

Handling uncertainties in SVM classification - Emilie Niaf; Rémi Flamary; Carole Lartizien; Stéphane Canu (CoRR, 2011)

Multi-modality image simulation with the Virtual Imaging Platform: Illustration on cardiac echography and MRI. - Tristan Glatard; Adrien Marion; Hugues Benoit-Cattin; Sorina Camarasu-Pop; Patrick Clarysse; Rafael Ferreira da Silva; Germain Forestier; Bernard Gibaud; Carole Lartizien; Hervé Liebgott; Kévin Moulin; Denis Friboulet (ISBI, 2012)

Computer aided staging of lymphoma patients with FDG PET/CT imaging based on textural information. - Carole Lartizien; Matthieu Rogez; Adeline Susset; Francesco Giammarile; Emilie Niaf; Fabien Ricard (ISBI, 2012)

Computer Aided Diagnosis of Intractable Epilepsy with MRI Imaging Based on Textural Information. - Meriem El Azami; Alexander Hammers; Nicolas Costes 001; Carole Lartizien (PRNI, 2013)

A Virtual Imaging Platform for Multi-Modality Medical Image Simulation. - Tristan Glatard; Carole Lartizien; Bernard Gibaud; Rafael Ferreira da Silva; Germain Forestier; Frederic Cervenansky; Martino Alessandrini; Hugues Benoit-Cattin; Olivier Bernard 001; Sorina Camarasu-Pop; Nadia Cerezo; Patrick Clarysse; et al. (IEEE Trans. Medical Imaging, 2013)

Robust outlier detection with L0-SVDD. - Meriem El Azami; Carole Lartizien; Stéphane Canu (ESANN, 2014)

Computer-aided diagnostic system for prostate cancer detection and characterization combining learned dictionaries and supervised classification. - Jérôme Lehaire; Rémi Flamary; Olivier Rouvière; Carole Lartizien (ICIP, 2014)

SVM with feature selection and smooth prediction in images: Application to CAD of prostate cancer. - Emilie Niaf; Rémi Flamary; Alain Rakotomamonjy; Olivier Rouvière; Carole Lartizien (ICIP, 2014)

OntoVIP: An ontology for the annotation of object models used for medical image simulation. - Bernard Gibaud; Germain Forestier; Hugues Benoit-Cattin; Frederic Cervenansky; Patrick Clarysse; Denis Friboulet; Alban Gaignard; Patrick Hugonnard; Carole Lartizien; Hervé Liebgott; Johan Montagnat; Joachim Tabary; et al. (J. Biomed. Informatics, 2014)

Kernel-Based Learning From Both Qualitative and Quantitative Labels: Application to Prostate Cancer Diagnosis Based on Multiparametric MR Imaging. - Emilie Niaf; Rémi Flamary; Olivier Rouvière; Carole Lartizien; Stéphane Canu (IEEE Trans. Image Process., 2014)

Computer-Aided Staging of Lymphoma Patients With FDG PET/CT Imaging Based on Textural Information. - Carole Lartizien; Matthieu Rogez; Emilie Niaf; Fabien Ricard (IEEE J. Biomed. Health Informatics, 2014)

Analyse psychophysique et apprentissage statistique pour l'aide au diagnostic en imagerie du cancer. - Carole Lartizien (2015)

Transfer Learning for Prostate Cancer Mapping Based on Multicentric MR Imaging Databases. - Rahaf Aljundi; Jérôme Lehaire; Fabrice Prost-Boucle; Olivier Rouvière; Carole Lartizien (MLMMI@ICML, 2015)

Combining multi-parametric MR images for the detection of epileptogenic lesions. - Meriem El Azami; Romain Bouet; Julien Jung; Alexander Hammers; Carole Lartizien (ISBI, 2015)

Converting SVDD scores into probability estimates. - Meriem El Azami; Carole Lartizien; Stéphane Canu (ESANN, 2016)

Converting SVDD scores into probability estimates: Application to outlier detection. - Meriem El Azami; Carole Lartizien; Stéphane Canu (Neurocomputing, 2017)

Unsupervised Feature Learning for Outlier Detection with Stacked Convolutional Autoencoders, Siamese Networks and Wasserstein Autoencoders: Application to Epilepsy Detection. - Zara Alaverdyan; Jiazheng Chai; Carole Lartizien (DLMIA/ML-CDS@MICCAI, 2018)

Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport. - Léo Gautheron; Ievgen Redko; Carole Lartizien (ECML/PKDD (2), 2018)

Feature extraction with regularized siamese networks for outlier detection: application to lesion screening in medical imaging. - Zara Alaverdyan; Carole Lartizien (CoRR, 2018)

Exploiting GPUs on distributed infrastructures for medical imaging applications with VIP and DIRAC. - Sorina Camarasu-Pop; Carole Lartizien; Thomas Grenier; Axel Bonnet; Pascal Wassong; Vanessa Hamar; Fabio Hernandez; Luisa Arrabito; Johan Bregeon; Pierre Gay; Andrei Tsaregorodtsev (MIPRO, 2019)

Deep Learning for Segmentation Using an Open Large-Scale Dataset in 2D Echocardiography. - Sarah Leclerc; Erik Smistad; João Pedrosa; Andreas Østvik; Frederic Cervenansky; Florian Espinosa; Torvald Espeland; Erik Andreas Rye Berg; Pierre-Marc Jodoin; Thomas Grenier; Carole Lartizien; Jan D'hooge; et al. (IEEE Trans. Medical Imaging, 2019)

Margin-aware Adversarial Domain Adaptation with Optimal Transport. - Sofien Dhouib; Ievgen Redko; Carole Lartizien (ICML, 2020)

Prostate Cancer Semantic Segmentation by Gleason Score Group in bi-parametric MRI with Self Attention Model on the Peripheral Zone. - Audrey Duran; Pierre-Marc Jodoin; Carole Lartizien (MIDL, 2020)

Priority U-Net: Detection of Punctuate White Matter Lesions in Preterm Neonate in 3D Cranial Ultrasonography. - Pierre Erbacher; Carole Lartizien; Matthieu Martin; Pedro Foletto-Pimenta; Philippe Quetin; Philippe Delachartre (MIDL, 2020)

LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography. - Sarah Leclerc; Erik Smistad; Andreas Østvik; Frederic Cervenansky; Florian Espinosa; Torvald Espeland; Erik Andreas Rye Berg; Thomas Grenier; Carole Lartizien; Pierre-Marc Jodoin; Lasse Løvstakken; Olivier Bernard 001 (CoRR, 2020)

Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening. - Zaruhi Alaverdyan; Julien Jung; Romain Bouet; Carole Lartizien (Medical Image Anal., 2020)

Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients. - Verónica Muñoz Ramírez; Nicolas Pinon; Florence Forbes; Carole Lartizien; Michel Dojat (MLCN@MICCAI, 2021)

GAN-Based Synthetic FDG PET Images from T1 Brain MRI Can Serve to Improve Performance of Deep Unsupervised Anomaly Detection Models. - Daria Zotova; Julien Jung; Carole Lartizien (SASHIMI@MICCAI, 2021)

Perfusion Imaging in Deep Prostate Cancer Detection from MP-MRI: Can We Take Advantage of it? - Audrey Duran; Gaspard Dussert; Carole Lartizien (ISBI, 2022)

Learning to segment prostate cancer by aggressiveness from scribbles in bi-parametric MRI. - Audrey Duran; Gaspard Dussert; Carole Lartizien (Image Processing, 2022)

ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans. - Audrey Duran; Gaspard Dussert; Olivier Rouvière; Tristan Jaouen; Pierre-Marc Jodoin; Carole Lartizien (Medical Image Anal., 2022)

Brain Subtle Anomaly Detection Based on Auto-Encoders Latent Space Analysis: Application To De Novo Parkinson Patients. - Nicolas Pinon; Geoffroy Oudoumanessah; Robin Trombetta; Michel Dojat; Florence Forbes; Carole Lartizien (ISBI, 2023)

Towards Frugal Unsupervised Detection of Subtle Abnormalities in Medical Imaging. - Geoffroy Oudoumanessah; Carole Lartizien; Michel Dojat; Florence Forbes (MICCAI (3), 2023)

Whole brain radiomics for clustered federated personalization in brain tumor segmentation. - Matthis Manthe; Stefan Duffner; Carole Lartizien (MIDL, 2023)

One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities. - Nicolas Pinon; Robin Trombetta; Carole Lartizien (MIDL, 2023)

Anomaly detection in image or latent space of patch-based auto-encoders for industrial image analysis. - Nicolas Pinon; Robin Trombetta; Carole Lartizien (CoRR, 2023)

Time CNN and Graph Convolution Network for Epileptic Spike Detection in Meg Data. - Pauline Mouches; Thibaut Dejean; Julien Jung; Romain Bouet; Carole Lartizien; Romain Quentin (ISBI, 2024)

Preface for International Conference on Medical Imaging with Deep Learning 2024. - Ninon Burgos; Caroline Petitjean; Maria Vakalopoulou; Stergios Christodoulidis; Pierrick Coupé; Hervé Delingette; Carole Lartizien; Diana Mateus (MIDL, 2024)

Weakly supervised deep learning model with size constraint for prostate cancer detection in multiparametric MRI and generalization to unseen domains. - Robin Trombetta; Olivier Rouvière; Carole Lartizien (MIDL, 2024)

Deep Domain Isolation and Sample Clustered Federated Learning for Semantic Segmentation. - Matthis Manthe; Carole Lartizien; Stefan Duffner (ECML/PKDD (4), 2024)

Federated brain tumor segmentation: An extensive benchmark. - Matthis Manthe; Stefan Duffner; Carole Lartizien (Medical Image Anal., 2024)

Fusion of Dwi Image and Clinical Variables for Stroke Outcome Prediction Using Tabular Transformer. - Mingtian Liu; Nima Hatami; Laura Mechtouff; Tae-Hee Cho; Carole Lartizien; Carole Frindel (ISBI, 2025)

Cluster Globally, Reduce Locally: Scalable Efficient Dictionary Compression for Magnetic Resonance Fingerprinting. - Geoffroy Oudoumanessah; Thomas Coudert; Luc Meyer; Aurélien Delphin; Thomas Christen; Michel Dojat; Carole Lartizien; Florence Forbes (ISBI, 2025)

GAN-based synthetic FDG PET images from T1 brain MRI can serve to improve performance of deep unsupervised anomaly detection models. - Daria Zotova; Nicolas Pinon; Robin Trombetta; Romain Bouet; Julien Jung; Carole Lartizien (Comput. Methods Programs Biomed., 2025)

Active MRI Acquisition with Diffusion Guided Bayesian Experimental Design. - Jacopo Iollo; Geoffroy Oudoumanessah; Carole Lartizien; Michel Dojat; Florence Forbes (CoRR, 2025)

OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection. - Nicolas Pinon; Carole Lartizien (CoRR, 2025)