Journal
RADIOLOGICAL PHYSICS AND TECHNOLOGY
Volume 10, Issue 1, Pages 23-32Publisher
SPRINGER JAPAN KK
DOI: 10.1007/s12194-017-0394-5
Keywords
Pulmonary image analysis; Computer-aided detection; Computer-aided diagnosis; Image processing; Machine learning; Deep learning
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available