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Published in: Radiological Physics and Technology 1/2017

Open Access 01-03-2017

Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning

Author: Bram van Ginneken

Published in: Radiological Physics and Technology | Issue 1/2017

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Abstract

Half a century ago, the term “computer-aided diagnosis” (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.
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Metadata
Title
Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning
Author
Bram van Ginneken
Publication date
01-03-2017
Publisher
Springer Japan
Published in
Radiological Physics and Technology / Issue 1/2017
Print ISSN: 1865-0333
Electronic ISSN: 1865-0341
DOI
https://doi.org/10.1007/s12194-017-0394-5

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