Comparison between traditional and deep learning-based semi-automatic segmentation methods for metastatic breast cancer lesions monitoring - Archive ouverte HAL
Communication Dans Un Congrès Année : 2020

Comparison between traditional and deep learning-based semi-automatic segmentation methods for metastatic breast cancer lesions monitoring

Domaines

Intelligence artificielle [cs.AI] Cancer

Noémie Moreau  : Connectez-vous pour contacter le contributeur

https://hal.science/hal-03639752

Soumis le : mercredi 13 avril 2022-09:32:41

Dernière modification le : mardi 27 août 2024-12:54:08

Fichier non déposé

Dates et versions

hal-03639752 , version 1 (13-04-2022)

Identifiants

  • HAL Id : hal-03639752 , version 1

Citer

Noémie Moreau, Caroline Rousseau, Ludovic Ferrer, Mario Campone, Mathilde Colombié, et al.. Comparison between traditional and deep learning-based semi-automatic segmentation methods for metastatic breast cancer lesions monitoring. 4th Nuclear Technologies for Health Symposium (NTHS2020), Feb 2020, Nantes, France. ⟨hal-03639752⟩

Exporter

BibTeX XML-TEI Dublin Core DC Terms EndNote DataCite

Collections

CNRS INRIA EC-NANTES UNAM LS2N LS2N-IPI NANTES-UNIVERSITE
25 Consultations
0 Téléchargements

Partager

More