Detection and characterization of MRI breast lesions using deep learning.

Journal: Diagnostic and interventional imaging

Published Date: Mar 26, 2019

Abstract

PURPOSE: The purpose of this study was to assess the potential of a deep learning model to discriminate between benign and malignant breast lesions using magnetic resonance imaging (MRI) and characterize different histological subtypes of breast lesions.

Authors

P Herent

Owkin Inc, Research and Development Laboratory, 75003 Paris, France.
B Schmauch

Owkin Inc, Research and Development Laboratory, 75003 Paris, France.
P Jehanno

Owkin Inc, Research and Development Laboratory, 75003 Paris, France. Electronic address: paul.jehanno@owkin.com.
O Dehaene

École Centrale d'Electronique (ECE), 75015 Paris, France.
C Saillard

Owkin Inc, Research and Development Laboratory, 75003 Paris, France.
C Balleyguier

Radiology Department, Institut Gustave-Roussy, 94805 Villejuif, France.
J Arfi-Rouche

Radiology Department, Institut Gustave-Roussy, 94805 Villejuif, France.
S Jégou

Owkin Inc, Research and Development Laboratory, 75003 Paris, France.

Keywords

Algorithms Breast Breast Neoplasms Contrast Media Datasets as Topic Deep Learning Female Gadolinium Humans Magnetic Resonance Imaging

External Resources

View on PubMed Access via DOI PubMed (30926444)

Detection and characterization of MRI breast lesions using deep learning.

Abstract

Authors

Keywords

External Resources

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