Machine learning approaches in medical image analysis: From detection to diagnosis
Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, lear...
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| Veröffentlicht in: | Medical image analysis 2016-10, Vol.33, p.94-97 |
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| container_end_page | 97 |
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| container_title | Medical image analysis |
| container_volume | 33 |
| creator | de Bruijne, Marleen |
| description | Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols, learning from weak labels, and interpretation and evaluation of results. |
| doi_str_mv | 10.1016/j.media.2016.06.032 |
| format | Article |
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| ispartof | Medical image analysis, 2016-10, Vol.33, p.94-97 |
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| language | eng |
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| source | MEDLINE; ScienceDirect Journals (5 years ago - present) |
| subjects | Algorithms Classification Computer aided diagnosis Diagnosis, Computer-Assisted Diagnostic Imaging Humans Machine Learning Transfer learning |
| title | Machine learning approaches in medical image analysis: From detection to diagnosis |
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