Prospects of deep learning for medical imaging
Machine learning techniques are essential components of medical imaging research. Recently, a highly flexible machine learning approach known as deep learning has emerged as a disruptive technology to enhance the performance of existing machine learning techniques and to solve previously intractable...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sungkyunkwan University School of Medi
2018-06-01
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| Series: | Precision and Future Medicine |
| Subjects: | |
| Online Access: | http://www.pfmjournal.org/upload/pdf/pfm-2018-00030.pdf |
| Summary: | Machine learning techniques are essential components of medical imaging research. Recently, a highly flexible machine learning approach known as deep learning has emerged as a disruptive technology to enhance the performance of existing machine learning techniques and to solve previously intractable problems. Medical imaging has been identified as one of the key research fields where deep learning can contribute significantly. This review article aims to survey deep learning literature in medical imaging and describe its potential for future medical imaging research. First, an overview of how traditional machine learning evolved to deep learning is provided. Second, a survey of the application of deep learning in medical imaging research is given. Third, wellknown software tools for deep learning are reviewed. Finally, conclusions with limitations and future directions of deep learning in medical imaging are provided. |
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| ISSN: | 2508-7940 2508-7959 |