Abstract
There has been a revolution in the past decade as “deep learning” has begun to show high performance with robust reliability in the real world for many imaging tasks. Current deep learning technologies are being applied to medical imaging tasks with good results, which has prompted great interest in applying them broadly into clinical practice. This chapter describes the basic principles of deep learning methods and some common applications in medical imaging.
Original language | English (US) |
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Title of host publication | Artificial Intelligence in Medicine |
Subtitle of host publication | Technical Basis and Clinical Applications |
Publisher | Elsevier Applied Science |
Pages | 19-34 |
Number of pages | 16 |
ISBN (Electronic) | 9780128212592 |
ISBN (Print) | 9780128212585 |
DOIs | |
State | Published - Jan 1 2020 |
Keywords
- Deep learning
- convolutional neural network
- fully connected network
- generative adversarial network
- loss function
- residual block
ASJC Scopus subject areas
- General Economics, Econometrics and Finance
- General Business, Management and Accounting