期刊
RADIOLOGICAL PHYSICS AND TECHNOLOGY
卷 10, 期 1, 页码 23-32出版社
SPRINGER JAPAN KK
DOI: 10.1007/s12194-017-0394-5
关键词
Pulmonary image analysis; Computer-aided detection; Computer-aided diagnosis; Image processing; Machine learning; Deep learning
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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