Frédéric Cervenansky
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View article: Editorial: Automatic methods for multiple sclerosis new lesions detection and segmentation
Editorial: Automatic methods for multiple sclerosis new lesions detection and segmentation Open
International audience
View article: Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure Open
We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and indepe…
View article: Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure Open
We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and indepe…
View article: ReproVIP: Enhancing Reproducibility of Scientific Results in Medical Imaging
ReproVIP: Enhancing Reproducibility of Scientific Results in Medical Imaging Open
Background : VIP (the Virtual Imaging Platform) is a web portal for medical imaging (MI) data analysis. By leveraging computational and storage resources from the EGI e-infrastructure, VIP provides MI researchers with end-user services to …
View article: MICCAI 2021 MSSEG-2 challenge demographics data
MICCAI 2021 MSSEG-2 challenge demographics data Open
This dataset will include all demographics and dataset constitution information for the MICCAI 2021 challenge.
View article: MICCAI 2021 MSSEG-2 challenge demographics data
MICCAI 2021 MSSEG-2 challenge demographics data Open
This dataset will include all demographics and dataset constitution information for the MICCAI 2021 challenge.
View article: MSSEG-2: A medical imaging challenge on VIP
MSSEG-2: A medical imaging challenge on VIP Open
International audience
View article: MICCAI 2021 MSSEG-2 challenge quantitative results
MICCAI 2021 MSSEG-2 challenge quantitative results Open
This dataset includes all quantitative results of all metrics for challengers of the MICCAI MSSEG2 2021 challenge on new MS lesions detection. It also includes the ranking excel file obtained on the challenge day. Please refer to the READM…
View article: MICCAI 2021 MSSEG-2 challenge quantitative results
MICCAI 2021 MSSEG-2 challenge quantitative results Open
This dataset includes all quantitative results of all metrics for challengers of the MICCAI MSSEG2 2021 challenge on new MS lesions detection. It also includes the ranking excel file obtained on the challenge day. Please refer to the READM…
View article: MICCAI 2021 MSSEG-2 challenge quantitative results
MICCAI 2021 MSSEG-2 challenge quantitative results Open
This dataset includes all quantitative results of all metrics for challengers of the MICCAI MSSEG2 2021 challenge on new MS lesions detection. It also includes the ranking excel file obtained on the challenge day. Please refer to the READM…
View article: MICCAI 2021 MSSEG-2 challenge quantitative results
MICCAI 2021 MSSEG-2 challenge quantitative results Open
This dataset includes all quantitative results of all metrics for challengers of the MICCAI MSSEG2 2021 challenge on new MS lesions detection. It also includes the ranking excel file obtained on the challenge day. Please refer to the READM…
View article: Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset
Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset Open
MRI plays a crucial role in multiple sclerosis diagnostic and patient follow-up. In particular, the delineation of T2-FLAIR hyperintense lesions is crucial although mostly performed manually - a tedious task. Many methods have thus been pr…
View article: MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure
MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segmentation challenge using a data management and processing infrastructure Open
International audience
View article: MICCAI 2016 challenge dataset demographics data
MICCAI 2016 challenge dataset demographics data Open
This dataset contains supplementary material for the 2016 MS segmentation challenge data article. It contains the full demographic data for the datasets opened to the public.
View article: MICCAI 2016 challenge dataset demographics data
MICCAI 2016 challenge dataset demographics data Open
This dataset contains supplementary material for the 2016 MS segmentation challenge data article. It contains the full demographic data for the datasets opened to the public.
View article: MICCAI 2016 challenge dataset demographics data
MICCAI 2016 challenge dataset demographics data Open
This dataset contains supplementary material for the 2016 MS segmentation challenge data article. It contains the full demographic data for the datasets opened to the public.
View article: Multiple sclerosis new lesions segmentation challenge
Multiple sclerosis new lesions segmentation challenge Open
MICCAI endorsed event Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system affecting more than half a million persons in Europe, with prevalence rate of 83 per 100 000 with higher rates in northern countr…
View article: LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography
LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography Open
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semiautomatically in clinical routine and is, thus, prone to interobserver and intraobserver varia…
View article: LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography
LU-Net: a multi-task network to improve the robustness of segmentation of left ventriclular structures by deep learning in 2D echocardiography Open
Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semi-automatically in clinical routine, and is thus prone to inter- and intra-observer variability…
View article: RU-Net: A refining segmentation network for 2D echocardiography
RU-Net: A refining segmentation network for 2D echocardiography Open
International audience
View article: Deep Learning Segmentation in 2D echocardiography using the CAMUS dataset : Automatic Assessment of the Anatomical Shape Validity
Deep Learning Segmentation in 2D echocardiography using the CAMUS dataset : Automatic Assessment of the Anatomical Shape Validity Open
We recently published a deep learning study on the potential of encoder-decoder networks for the segmentation of the 2D CAMUS ultrasound dataset. We propose in this abstract an extension of the evaluation criteria to anatomical assessment,…
View article: Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure Open
We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and indepe…
View article: Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure
Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure Open
We present a study of multiple sclerosis segmentation algorithms conducted at the international MICCAI 2016 challenge. This challenge was operated using a new open-science computing infrastructure. This allowed for the automatic and indepe…
View article: Miccai 2016 Ms Lesion Segmentation Challenge: Supplementary Results
Miccai 2016 Ms Lesion Segmentation Challenge: Supplementary Results Open
This package contains supplementary material for our article prepared for publication and under revision. It contains omitted results due to space limits of the article as well as detailed, patient per patient and team per team results for…
View article: Miccai 2016 Ms Lesion Segmentation Challenge: Supplementary Results
Miccai 2016 Ms Lesion Segmentation Challenge: Supplementary Results Open
This package contains supplementary material for our article prepared for publication and under revision. It contains omitted results due to space limits of the article as well as detailed, patient per patient and team per team results for…
View article: Boutiques: a flexible framework to integrate command-line applications in computing platforms
Boutiques: a flexible framework to integrate command-line applications in computing platforms Open
We present Boutiques, a system to automatically publish, integrate, and execute command-line applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSO…
View article: Boutiques: a flexible framework for automated application integration in computing platforms
Boutiques: a flexible framework for automated application integration in computing platforms Open
We present Boutiques, a system to automatically publish, integrate and execute applications across computational platforms. Boutiques applications are installed through software containers described in a rich and flexible JSON language. A …
View article: misoSR: Medical Image Isotropic Super-Resolution Reconstruction
misoSR: Medical Image Isotropic Super-Resolution Reconstruction Open
International audience