Classification of microcalcification clusters in digital breast tomosynthesis using ensemble convolutional neural network

Classification of microcalcification clusters in digital breast tomosynthesis using ensemble convolutional neural network

Abstract Background The classification of benign and malignant microcalcification clusters (MCs) is an important task for computer-aided diagnosis (CAD) of digital breast tomosynthesis (DBT) images. Influenced by imaging method, DBT has the characteristic of anisotropic resolution, in which the reso...

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Bibliographic Details
Main Authors: Bingbing Xiao, Haotian Sun, You Meng, Yunsong Peng, Xiaodong Yang, Shuangqing Chen, Zhuangzhi Yan, Jian Zheng
Format: Article
Language:English
Published: BMC 2021-07-01
Series:BioMedical Engineering OnLine
Subjects:
Microcalcification cluster
Digital breast tomosynthesis
Convolution neural network
Ensemble learning
Classification
Online Access:https://doi.org/10.1186/s12938-021-00908-1

Internet

https://doi.org/10.1186/s12938-021-00908-1

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