Evaluating the performance of convolutional neural networks with direct acyclic graph architectures in automatic segmentation of breast lesion in US images

Evaluating the performance of convolutional neural networks with direct acyclic graph architectures in automatic segmentation of breast lesion in US images

Abstract Background Outlining lesion contours in Ultra Sound (US) breast images is an important step in breast cancer diagnosis. Malignant lesions infiltrate the surrounding tissue, generating irregular contours, with spiculation and angulated margins, whereas benign lesions produce contours with a...

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Bibliographic Details
Main Authors: Marly Guimarães Fernandes Costa, João Paulo Mendes Campos, Gustavo de Aquino e Aquino, Wagner Coelho de Albuquerque Pereira, Cícero Ferreira Fernandes Costa Filho
Format: Article
Language:English
Published: BMC 2019-11-01
Series:BMC Medical Imaging
Subjects:
Breast lesion
Ultrasound images
Convolutional neural networks
Online Access:http://link.springer.com/article/10.1186/s12880-019-0389-2

Internet

http://link.springer.com/article/10.1186/s12880-019-0389-2

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