Applied Machine Learning in Spiral Breast-CT: Can We Train a Deep Convolutional Neural Network for Automatic, Standardized and Observer Independent Classification of Breast Density?

Applied Machine Learning in Spiral Breast-CT: Can We Train a Deep Convolutional Neural Network for Automatic, Standardized and Observer Independent Classification of Breast Density?

The aim of this study was to investigate the potential of a machine learning algorithm to accurately classify parenchymal density in spiral breast-CT (BCT), using a deep convolutional neural network (dCNN). In this retrospectively designed study, 634 examinations of 317 patients were included. After...

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Bibliographic Details
Main Authors: Anna Landsmann, Jann Wieler, Patryk Hejduk, Alexander Ciritsis, Karol Borkowski, Cristina Rossi, Andreas Boss
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Diagnostics
Subjects:
spiral breast-CT
photon counting breast-CT
machine learning
artificial intelligence
Online Access:https://www.mdpi.com/2075-4418/12/1/181

Internet

https://www.mdpi.com/2075-4418/12/1/181

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