Carole Lartizien

Orcid: 0000-0001-7594-4231

According to our database1, Carole Lartizien authored at least 44 papers between 2004 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Time CNN and Graph Convolution Network for Epileptic Spike Detection in MEG Data.
CoRR, 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

Towards Frugal Unsupervised Detection of Subtle Abnormalities in Medical Imaging.
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

Margin-aware Adversarial Domain Adaptation with Optimal Transport.
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

Feature Selection for Unsupervised Domain Adaptation Using Optimal Transport.
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
Converting SVDD scores into probability estimates: Application to outlier detection.
Neurocomputing, 2017

2016
Converting SVDD scores into probability estimates.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Combining multi-parametric MR images for the detection of epileptogenic lesions.
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

Robust outlier detection with L0-SVDD.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
A Virtual Imaging Platform for Multi-Modality Medical Image Simulation.
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
Handling uncertainties in SVM classification
CoRR, 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
Comparison of Bootstrap Resampling Methods for 3-D PET Imaging.
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
Effect of Scan Duration on Lesion Detectability in PET Oncology Imaging.
Proceedings of the 2004 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2004


  Loading...