Automatic and standardized quality assurance of digital mammography and tomosynthesis with deep convolutional neural networks

被引：0
作者：
Patryk Hejduk
Raphael Sexauer
Carlotta Ruppert
Karol Borkowski
Jan Unkelbach
Noemi Schmidt
机构：
[1] University Hospital Zurich,Institute of Diagnostic and Interventional Radiology
[2] University Hospital Basel,Breast Imaging, Radiology and Nuclear Medicine
[3] University Hospital Zurich,Department of Radiation Oncology
来源：
Insights into Imaging | / 14卷
关键词：
Mammography; Tomosynthesis; Quality control; Machine learning; Artificial intelligence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Deep convolutional neural network (dCNN) models have been trained for classification of mammography imaging quality features.AI can reliably classify diagnostic image quality of mammography and tomosynthesis.Quality control of mammography and tomosynthesis can be automated.
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