A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets

Background Deep learning methods for radiomics/computer‐aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing. Aims We aim to develop a breast CADx methodology that addresses the aforementioned issues by exploiting the ef...

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Bibliographic Details

Published in:	Medical physics (Lancaster) Vol. 44; no. 10; pp. 5162 - 5171
Main Authors:	Antropova, Natalia, Huynh, Benjamin Q., Giger, Maryellen L.
Format:	Journal Article
Language:	English
Published:	United States 01.10.2017
Subjects:	breast cancer Breast Neoplasms - diagnostic imaging deep learning Diagnosis, Computer-Assisted - methods feature extraction Humans Image Processing, Computer-Assisted - methods Neural Networks (Computer) Retrospective Studies ROC Curve deep learning feature extraction breast cancer
ISSN:	0094-2405, 2473-4209, 2473-4209
Online Access:	Get full text
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